|
FrP1 |
Roselle Simpor Main Ballroom 4601AB-4806 |
Machine Learning: Bane or Boon for Control? |
Plenary Session |
Chair: Parisini, Thomas | Imperial College & Univ. of Trieste |
|
08:30-09:30, Paper FrP1.1 | |
>Machine Learning: Bane or Boon for Control? |
|
Krstic, Miroslav | University of California, San Diego |
Keywords: Machine learning
Abstract: Control theory is hardly alone among scientific communities experiencing some “obsolescence anxiety” in the face of machine learning, where decades - or centuries - of building first-principles models and designs are supplanted by data. While ML real-time feedback is unlikely to attain the adaptive control’s closed-loop guarantees for unstable plants that lack persistency of excitation, our community, adept at harnessing new ideas, has generated in a few years many other adoit ways to incorporate ML - from lightening methodological complexities to circumventing difficult constructions. Rather than walking away from certificate-bearing control tools built by generations of control researchers, in this lecture I seek game-changing “supporting roles” for ML, in control implementation. I present the emerging subject of employing the latest breakthrough in deep learning approximations of not functions but function-to-function mappings (nonlinear operators) in the complex field of PDE control. With “neural operators,” entire PDE control methodologies are encoded into what amounts to a function evaluation, leading to a thousandfold speedup and enabling PDE control implementations. Deep neural operators, such as DeepONet, mathematically guaranteed to provide an arbitrarily close accuracy in rapidly computing control inputs, preserve the stabilization guarantees of the existing PDE backstepping controllers. Applications range from traffic and epidemiology to manufacturing, energy generation, and supply chains.
|
|
FrA01 |
Melati Junior 4010A-4111 |
Learning, Optimization, and Game Theory III |
Invited Session |
Chair: Vamvoudakis, Kyriakos G. | Georgia Inst. of Tech |
Co-Chair: Zhang, Kaiqing | University of Maryland |
Organizer: Doan, Thinh T. | Virginia Tech |
Organizer: Sayin, Muhammed Omer | Bilkent University |
Organizer: Vamvoudakis, Kyriakos G. | Georgia Inst. of Tech |
Organizer: Zhang, Kaiqing | University of Maryland |
|
10:00-10:20, Paper FrA01.1 | |
>Approximate Optimal Indirect Regulation of an Uncertain Agent with a Lyapunov-Based Deep Neural Network |
|
Makumi, Wanjiku A. | University of Florida |
Bell, Zachary I. | Air Force |
Dixon, Warren E. | University of Florida |
Keywords: Nonlinear systems identification, Lyapunov methods, Machine learning
Abstract: An approximate optimal policy is developed for a pursuing agent to indirectly regulate an evading agent coupled by an uncertain interaction dynamic. Approximate dynamic programming is used to design a controller for the pursuing agent to optimally influence the evading agent to a goal location. Since the interaction dynamic between the agents is unknown, integral concurrent learning is used to update a Lyapunov-based deep neural network to facilitate sustained learning and system identification. A Lyapunov-based stability analysis is used to show uniformly ultimately bounded convergence. Simulation results demonstrate the performance of the developed method.
|
|
10:20-10:40, Paper FrA01.2 | |
>Neural Operators for Hyperbolic PDE Backstepping Feedback Laws (I) |
|
Bhan, Luke | University of California, San Diego |
Shi, Yuanyuan | University of California San Diego |
Krstic, Miroslav | University of California, San Diego |
Keywords: Nonlinear output feedback, Learning, Nonlinear systems
Abstract: We introduce a framework for accelerating the computation of a backstepping controller in PDE control. We learn the nonlinear operator from the plant parameter and PDE solution to the boundary control with a (deep) neural network. We provide closed-loop stability guarantees (semiglobal exponential) under a NN-approximation of the feedback law. While, in the existing PDE backstepping, finding a feedback law requires the solution to multiple integral equations and operations for both the gain and control input value, the neural operator (NO) approach we propose learns the mapping from the functional coefficients of the plant PDE and PDE system state to the boundary control value by employing a sufficiently high number of offline numerical solutions to the analytical feedback control law. We prove the existence of a DeepONet approximation with arbitrarily high accuracy, of the exact nonlinear continuous operator mapping between the PDE coefficient functions and PDE system state into a control feedback law. Once proven to exist, learning of the NO is standard, completed "once and for all" (never online) and the control feedback equation doesn't need to be solved ever again, for both any new functional coefficient and PDE system state that does not exceed the magnitude of the coefficients and states used in training. Simulation illustrations are provided and the code is available on github.
|
|
10:40-11:00, Paper FrA01.3 | |
>On the Effect of the Presence of an Opponent in a Class of LQ Differential Games (I) |
|
Tarantino, Lorenzo | Università Degli Studi Di Roma Tor Vergata |
Astolfi, Alessandro | Imperial College & Univ. of Rome |
Sassano, Mario | University of Rome, Tor Vergata |
Keywords: Optimal control, Optimization, Nonlinear systems
Abstract: The aim of this paper is to assess the effect of the presence of an opponent in a class of finite-horizon differential games described by scalar linear differential equations and quadratic cost functionals in which the state is penalized only at the terminal time. The contribution of the other player is quantitatively characterized by comparing the solutions of the underlying Riccati differential equations for the optimal control (in the absence of the opponent) and of the differential game. In the case of open-loop Nash equilibria, this effect can be characterized in closed form, since an analytic expression for the solutions of the coupled asymmetric differential Riccati equations can be computed. For feedback Nash equilibria a closed-form solution to the related coupled symmetric differential Riccati equations cannot be determined. Therefore an estimate of the solution is provided by relying on a functional approximation approach, allowing to characterize the effect of the presence of an opponent also in this setting.
|
|
11:00-11:20, Paper FrA01.4 | |
>Learning Switched Koopman Models for Control of Entity-Based Systems (I) |
|
Blischke, Madeline | The University of California, Santa Barbara |
Hespanha, Joao P. | Univ. of California, Santa Barbara |
Keywords: Data driven control, Learning, Optimal control
Abstract: One problem that arises in control engineering is that of controlling a system for which the dynamics are unknown. Such a problem favors a data-driven approach, such as can be done through the use of the Koopman operator. We present a switched Koopman model, applicable to systems with discrete sets of inputs, that gives rise to an optimal control problem with a piecewise affine value function. This structure provides an efficient representation and enables a heuristic pruning algorithm that avoids the exponential complexity of finding the true optimal solution. We use density-like observables that are defined through the notion of entity-based systems: systems whose state is composed of a possibly varying number of entities that can be grouped into classes of like-entities. This encompasses many systems, including arcade games, a common benchmark used in reinforcement learning. We find that our approach requires much less training than commonly used for reinforcement learning. The Koopman approach also has the advantage of being agnostic to the control objective, which allows the objective to be changed without needing to retrain the model.
|
|
11:20-11:40, Paper FrA01.5 | |
>A Physics-Informed Neural Networks Framework to Solve the Infinite-Horizon Optimal Control Problem (I) |
|
Fotiadis, Filippos | Georgia Institute of Technology |
Vamvoudakis, Kyriakos G. | Georgia Inst. of Tech |
Keywords: Neural networks, Optimal control, Learning
Abstract: In this work, we leverage physics-informed neural networks (PINNs) to approximately solve the infinite-horizon optimal control problem for nonlinear systems. Specifically, since PINNs are generally able to solve a class of partial differential equations, they can be employed to approximate the value function in the infinite-horizon optimal control problem, via solving the associated steady-state Hamilton-Jacobi-Bellman (HJB) equation. However, the issue with such a direct approach is that the steady HJB equation generally yields more than one solution, hence directly employing PINNs to solve it can lead to divergence of the method. To tackle this problem, we instead apply PINNs to a finite-horizon variant of the steady-state HJB equation which has a unique solution, and which uniformly approximates the infinite-horizon optimal value function as the horizon increases. A method to verify whether the selected horizon is large enough is also provided, as well as an algorithm to increase it with reduced computations if it is not. Unlike conventional methods, the proposed approach does not require knowledge of a stabilizing controller, the execution of computationally expensive iterations, or polynomial basis functions for approximation.
|
|
11:40-12:00, Paper FrA01.6 | |
>Worst-Case Control and Learning Using Partial Observations Over an Infinite Time Horizon (I) |
|
Dave, Aditya | Cornell University |
Faros, Ioannis | University of Delaware |
Senthil Kumar, Nishanth Venkatesh | Cornell University |
Malikopoulos, Andreas A. | Cornell University |
Keywords: Machine learning, Robust control, Uncertain systems
Abstract: Safety-critical cyber-physical systems require control strategies whose worst-case performance is robust against adversarial disturbances and modeling uncertainties. In this paper, we present a framework for approximate control and learning in partially observed systems to minimize the worst-case discounted cost over an infinite time horizon. We model disturbances to the system as finite-valued uncertain variables with unknown probability distributions. For problems with known system dynamics, we construct a dynamic programming (DP) decomposition to compute the optimal control strategy. Our first contribution is to define information states that improve the computational tractability of this DP for a class of problems with observable incurred costs at each time instance. Our second contribution proposes approximate information states that can be constructed or learned directly from observed data for these problems. We derive bounds on the performance loss of the resulting approximate control strategy and illustrate the effectiveness of our approach in partially observed decision-making problems with a numerical example.
|
|
FrA02 |
Orchid Main 4202-4303 |
Data-Driven Verification and Control of Cyber-Physical Systems I |
Invited Session |
Chair: Lavaei, Abolfazl | Newcastle University |
Co-Chair: Jungers, Raphaël M. | University of Louvain |
Organizer: Lavaei, Abolfazl | Newcastle University |
Organizer: Jungers, Raphaël M. | University of Louvain |
Organizer: Abate, Alessandro | University of Oxford |
|
10:00-10:20, Paper FrA02.1 | |
>Data-Driven Stability Certificate of Interconnected Homogeneous Networks Via ISS Properties |
|
Lavaei, Abolfazl | Newcastle University |
Angeli, David | Imperial College |
Keywords: Stability of nonlinear systems, Network analysis and control, Large-scale systems
Abstract: This letter is concerned with a compositional data-driven approach for stability certificate of interconnected homogeneous networks with (partially) unknown dynamics while providing 100% correctness guarantees (as opposed to probabilistic confidence). The proposed framework enjoys input-to-state stability (ISS) properties of subsystems described by ISS Lyapunov functions. In our data-driven scheme, we first reformulate the corresponding conditions of ISS Lyapunov functions as a robust optimization program (ROP). Due to appearing unknown dynamics of subsystems in the constraint of ROP, we propose a scenario optimization program (SOP) by collecting data from trajectories of each unknown subsystem. We solve SOP and construct an ISS Lyapunov function for each subsystem with unknown dynamics. We accordingly leverage a compositional technique based on max-type small-gain reasoning and construct a Lyapunov function for an unknown interconnected network based on ISS Lyapunov functions of individual subsystems. We demonstrate the efficacy of our data-driven approach over a room temperature network containing 1000 rooms with unknown dynamics. Given collected data from each unknown room, we verify that the unknown interconnected network is globally asymptotically stable (GAS) with 100% correctness guarantee.
|
|
10:20-10:40, Paper FrA02.2 | |
>Data-Driven Control with Inherent Lyapunov Stability (I) |
|
Min, Youngjae | MIT |
Richards, Spencer M. | Stanford University |
Azizan, Navid | MIT |
Keywords: Data driven control, Lyapunov methods, Machine learning
Abstract: Recent advances in learning-based control leverage deep function approximators, such as neural networks, to model the evolution of controlled dynamical systems over time. However, the problem of learning a dynamics model and a stabilizing controller persists, since the synthesis of a stabilizing feedback law for known nonlinear systems is a difficult task, let alone for complex parametric representations that must be fit to data. To this end, we propose Control with Inherent Lyapunov Stability (CoILS), a method for jointly learning parametric representations of a nonlinear dynamics model and a stabilizing controller from data. To do this, our approach simultaneously learns a parametric Lyapunov function which intrinsically constrains the dynamics model to be stabilizable by the learned controller. In addition to the stabilizability of the learned dynamics guaranteed by our novel construction, we show that the learned controller stabilizes the true dynamics under certain assumptions on the fidelity of the learned dynamics. Finally, we demonstrate the efficacy of CoILS on a variety of simulated nonlinear dynamical systems.
|
|
10:40-11:00, Paper FrA02.3 | |
>Data-Driven Abstractions Via Adaptive Refinements and a Kantorovich Metric (I) |
|
Banse, Adrien | UCLouvain |
Romao, Licio | University of Oxford |
Abate, Alessandro | University of Oxford |
Jungers, Raphaël M. | University of Louvain |
Keywords: Sampled-data control, Iterative learning control, Behavioural systems
Abstract: We introduce an adaptive refinement procedure for smart and scalable abstraction of dynamical systems. Our technique relies on partitioning the state space depending on the observation of future outputs. However, this knowledge is dynamically constructed in an adaptive, asymmetric way. In order to learn the optimal structure, we define a Kantorovich-inspired metric between Markov chains, and we use it to guide the state partition refinement. Our technique is prone to data-driven frameworks, but not restricted to. We also study properties of the above mentioned metric between Markov chains, which we believe could be of broader interest. We propose an algorithm to approximate it, and we show that our method yields a much better computational complexity than using classical linear programming techniques.
|
|
11:00-11:20, Paper FrA02.4 | |
>Contraction-Guided Adaptive Partitioning for Reachability Analysis of Neural Network Controlled Systems (I) |
|
Harapanahalli, Akash | Georgia Institute of Technology |
Jafarpour, Saber | Georgia Institute of Technology |
Coogan, Samuel | Georgia Institute of Technology |
Keywords: Neural networks, Autonomous systems, Nonlinear systems
Abstract: In this paper, we present a contraction-guided adaptive partitioning algorithm for improving interval-valued robust reachable set estimates in a nonlinear feedback loop with a neural network controller and disturbances. Based on an estimate of the contraction rate of over-approximated intervals, the algorithm chooses when and where to partition. Then, by leveraging a decoupling of the neural network verification step and reachability partitioning layers, the algorithm can provide accuracy improvements for little computational cost. This approach is applicable with any sufficiently accurate open-loop interval-valued reachability estimation technique and any method for bounding the input-output behavior of a neural network. Using contraction-based robustness analysis, we provide guarantees of the algorithm's performance with mixed monotone reachability. Finally, we demonstrate the algorithm's performance through several numerical simulations and compare it with existing methods in the literature. In particular, we report a sizable improvement in the accuracy of reachable set estimation in a fraction of the runtime as compared to state-of-the-art methods.
|
|
11:20-11:40, Paper FrA02.5 | |
>Certified Vision-Based State Estimation for Autonomous Landing Systems Using Reachability Analysis (I) |
|
Santa Cruz Leal, Ulices | University of California Irvine |
Shoukry, Yasser | University of California, Irvine |
Keywords: Formal Verification/Synthesis, Vision-based control, Machine learning
Abstract: This paper studies the problem of designing a certified vision-based state estimator for autonomous landing systems. In such a system, a neural network (NN) processes images from a camera to estimate the aircraft's relative position with respect to the runway. We propose an algorithm to design such NNs with certified properties in terms of their ability to detect runways and provide accurate state estimation. At the heart of our approach is the use of geometric models of perspective cameras to obtain a mathematical model that captures the relation between the aircraft states and the inputs. We show that such geometric models enjoy mixed monotonicity properties that can be used to design state estimators with certifiable error bounds. We show the effectiveness of the proposed approach using an experimental testbed on data collected from event-based cameras.
|
|
11:40-12:00, Paper FrA02.6 | |
>MDP Abstractions from Data: Large-Scale Stochastic Networks (I) |
|
Lavaei, Abolfazl | Newcastle University |
Keywords: Stochastic systems, Data driven control, Network analysis and control
Abstract: This work proposes a compositional data-driven technique for the construction of finite Markov decision processes (MDPs) for large-scale stochastic networks with unknown mathematical models. Our proposed framework leverages dissipativity properties of subsystems and their finite MDPs using a notion of stochastic storage functions (SStF). In our data-driven scheme, we first build an SStF between each unknown subsystem and its data-driven finite MDP with a certified probabilistic confidence. We then derive dissipativity-type compositional conditions to construct a stochastic bisimulation function (SBF) between an interconnected network and its finite MDP using data-driven SStF of subsystems. Accordingly, we formally quantify the probabilistic distance between trajectories of an unknown large-scale stochastic network and those of its finite MDP with a guaranteed confidence. We illustrate the efficacy of our data-driven results over a room temperature network composing 100 rooms with unknown models.
|
|
FrA03 |
Orchid Main 4204-4305 |
Safe Planning and Control with Uncertainty Quantification III |
Invited Session |
Chair: Gao, Yulong | University of Oxford |
Co-Chair: Motee, Nader | Lehigh University |
Organizer: Gao, Yulong | University of Oxford |
Organizer: Lindemann, Lars | University of Southern California |
Organizer: Fan, Chuchu | Massachusetts Institute of Technology |
Organizer: Abate, Alessandro | University of Oxford |
Organizer: Pappas, George J. | University of Pennsylvania |
|
10:00-10:20, Paper FrA03.1 | |
>Safe Navigation of Networked Robots under Localization Uncertainty Using Robust Control Barrier Functions (I) |
|
Miksits, Adam | Ericsson Research |
Barbosa, Fernando | Ericsson Research |
Lindhé, Magnus | Ericsson Research |
Araujo, Jose | Ericsson Research |
Johansson, Karl H. | KTH Royal Institute of Technology |
Keywords: Robotics, Autonomous robots, Uncertain systems
Abstract: 5G networks have the potential to provide external sensor data and offload computations for future industrial mobile robots. To enable these benefits while maintaining safety, we propose a modular architecture, including an onboard safety filter for the velocity control loop. The safety filter leverages robust control barrier functions to guarantee safety from collisions under bounded localization uncertainty. Initial experiments are performed to quantify the localization uncertainty and generate suitable bounds for the safety filter. We then derive the safety filter, and analyze its conservatism numerically. Finally, the method is demonstrated in experiments using an ABB Mobile YuMi® Research Platform robot.
|
|
10:20-10:40, Paper FrA03.2 | |
>Safe Perception-Based Control under Stochastic Sensor Uncertainty Using Conformal Prediction (I) |
|
Yang, Shuo | University of Pennsylvania |
Pappas, George J. | University of Pennsylvania |
Mangharam, Rahul | University of Pennsylvania |
Lindemann, Lars | University of Southern California |
Keywords: Vision-based control, Machine learning, Autonomous systems
Abstract: We consider perception-based control using state estimates that are obtained from high-dimensional sensor measurements via learning-enabled perception maps. However, these perception maps are not perfect and result in state estimation errors that can lead to unsafe system behavior. Stochastic sensor noise can make matters worse and result in estimation errors that follow unknown distributions. We propose a perception-based control framework that i) quantifies estimation uncertainty of perception maps, and ii) integrates these uncertainty representations into the control design. To do so, we use conformal prediction to compute valid state estimation regions, which are sets that contain the unknown state with high probability. We then devise a sampled-data controller for continuous-time systems based on the notion of measurement robust control barrier functions. Our controller uses idea from self-triggered control and enables us to avoid using stochastic calculus. Our framework is agnostic to the choice of the perception map, independent of the noise distribution, and to the best of our knowledge the first to provide probabilistic safety guarantees in such a setting. We demonstrate the effectiveness of our proposed perception-based controller for a LiDAR-enabled F1/10th car.
|
|
10:40-11:00, Paper FrA03.3 | |
>Data-Driven IQC-Based Robust Control Design for Hybrid Micro-Disturbance Isolation Platform (I) |
|
Gupta, Vaibhav | École Polytechnique Fédérale De Lausanne (EPFL) |
Klauser, Elias | CSEM SA |
Karimi, Alireza | EPFL |
Keywords: Control applications, Data driven control, Uncertain systems
Abstract: A novel approach for robust controller synthesis, which models uncertainty as an elliptical set, is proposed in the paper. Given a set of frequency response functions of linear time-invariant (LTI) multiple-input multiple-output (MIMO) systems, the approach determines the `best' linear nominal model and the corresponding elliptical uncertainty set, which is consistent with the data. Using a novel split representation, the uncertainty set is represented as an equivalent integral quadratic constraint (IQC). Finally, this IQC is integrated into a data-driven frequency-domain controller synthesis method using convex optimisation. The proposed method is used to design a controller, which is robust against mechanical uncertainties, for a hybrid micro-disturbance isolation platform for space applications. The experimental results show that the proposed method provides a `tighter' uncertainty set and improves attenuation performance compared to classical methods that use disk uncertainty.
|
|
11:00-11:20, Paper FrA03.4 | |
>Impact of Misperception on Emergence of Risk in Platoon of Autonomous Vehicles (I) |
|
Amini, Arash | The University of Texas at Austin |
Liu, Guangyi | Lehigh University |
Pandey, Vivek | Lehigh University |
Motee, Nader | Lehigh University |
Keywords: Network analysis and control, Networked control systems, Autonomous vehicles
Abstract: The emergence of advanced perception algorithms has opened the possibility of achieving long-term autonomy in vehicle platooning. We develop a framework to assess the risk of misperception due to noisy observations from the environment. Each vehicle is assumed to rely on a perception unit to comprehend its surrounding environment and estimate other vehicles' positions and velocity. The Expected Shortfall (Average Value-at-Risk) measure is employed to assess the risk of collision between vehicle pairs and the risk of violating traffic laws for each vehicle under possible misperceptions. Obtaining an explicit expression for the risk measure allows us to further explore the potential trade-offs between the overall misperception-induced risks and network architecture. Using our framework, we demonstrate how misperception of highway traffic signs may cause phenomena similar to tailgating and quantify how it affects the risk of such events. Our result can also be applied to identify vehicles with high fragility to misperception and to increase the robustness of the platoon concerning overall risk measures in the presence of misperception. Our theoretical results are validated by extensive simulation.
|
|
11:20-11:40, Paper FrA03.5 | |
>Formal Verification of Attitude Control Systems Using Geometric Barrier Functions (I) |
|
Xu, Chencheng | Zhejiang University |
Zhao, Chengcheng | Zhejiang University |
Shi, Zhiguo | Zhejiang Univesity |
Chen, Jiming | Zhejiang University |
Keywords: Formal Verification/Synthesis, Autonomous robots
Abstract: Compared to safe obstacle avoidance in the position space, ensuring the safety of the attitude system in today's aerial vehicle operations is more challenging due to the non-Euclidean nature of the attitude space and the underactuated nature of the system. To address this issue, we first propose a Geometric Exponential Barrier Condition (GEBC) to produce barrier certificates on the manifold, by which attitude safety requirements can be encoded globally into the verification problems of attitude control systems. Then, we use exponential coordinates to characterize GEBCs, which makes them descriable in terms of Quantifier Free Real Arithmetic Logic (QF-NRA) and efficiently solvable by SMT solvers. A performance criterion is further discussed where we propose an effective algorithm to construct safe operational regions with different controllers, which can help with nominal controller selection and tuning. Finally, we demonstrate our approach in a quadrotor system and analyze the safe performance of two PD controllers on the proposed safe operation criteria.
|
|
11:40-12:00, Paper FrA03.6 | |
>Controller Implementability: A Data-Driven Approach (I) |
|
Padoan, Alberto | ETH Zürich |
Coulson, Jeremy | University of Wisconsin-Madison |
Dörfler, Florian | Swiss Federal Institute of Technology (ETH) Zurich |
Keywords: Linear systems, Identification for control, Optimal control
Abstract: We study the controller implementability problem, which seeks to determine if a controller can make the closed-loop behavior of a given plant match that of a desired reference behavior. We establish necessary and sufficient conditions for controller implementability which only rely on raw data. Subsequently, we consider the problem of constructing controllers directly from data. By leveraging the concept of canonical controller, we provide a formula to directly construct controllers that implement plant-compatible reference behaviors using measurements of both reference and plant behaviors.
|
|
FrA04 |
Simpor Junior 4913 |
Autonomous Vehicles II |
Regular Session |
Chair: Axehill, Daniel | Linköping University |
Co-Chair: Chen, Ben M. | Chinese University of Hong Kong |
|
10:00-10:20, Paper FrA04.1 | |
>Scenario-Based Hybrid Model Predictive Design for Cooperative Adaptive Cruise Control in Mixed-Autonomy Environments |
|
Mosharafian, Sahand | University of Georgia |
Bao, Yajie | The University of Georgia |
Mohammadpour Velni, Javad | Clemson University |
Keywords: Autonomous vehicles, Hybrid systems, Stochastic optimal control
Abstract: This paper presents a scenario-based hybrid model predictive control (MPC) design approach for cooperative adaptive cruise control (CACC) in mixed-autonomy traffic environments with uncertainties stemming from unexpected maneuvers of human-driven vehicles. Different from the past works that consider one possible realization of uncertainty, the proposed approach here considers multiple scenarios based on the uncertainty description that varies with the relative location of the human-driven vehicles (HVs) and the connected and automated vehicles (CAVs). For each scenario, a mixed integer quadratic programming problem is formulated for the control of CAVs with four operating modes, namely free following, braking, danger, and lane change. Each CAV's operating mode is determined based on the predictive information it receives from its predecessors and the anticipated behaviors of surrounding HVs. All the scenarios are handled simultaneously using the scenario-based MPC approach for a robust CACC. Simulations in a mixed-autonomy traffic system including two lanes demonstrate that the proposed scenario-based hybrid MPC approach significantly reduces deviations from the desired spacing policy and the desired velocity in the platoon during unexpected human-driven vehicle maneuvers, compared with the past work, particularly, a discrete hybrid stochastic (DHSA) MPC approach.
|
|
10:20-10:40, Paper FrA04.2 | |
>Energy-Optimal Trajectory-Based Traveling Salesman Problem for Multi-Rotor Unmanned Aerial Vehicles |
|
Gao, Chuanxiang | The Chinese University of Hong Kong |
Ding, Wendi | The Chinese University of Hong Kong |
Zuoquan, Zhao | The Chinese University of Hong Kong |
Chen, Ben M. | Chinese University of Hong Kong |
Keywords: Autonomous vehicles, Optimization, Evolutionary computing
Abstract: The trajectory-based traveling salesman problem represents an extension of the classical traveling salesman problem, aimed at determining the most optimal trajectory that passes through a designated set of points. This paper introduces a novel formulation, termed the Energy-Optimal Trajectory-Based Traveling Salesman Problem (EOTB-TSP), which is grounded in an innovative energy assessment model. This model takes into account the intricate dynamics of unmanned aerial vehicles (UAVs). In addition, the EOTB-TSP is cast as a bilevel optimization challenge. To tackle this complex problem, we introduce a modified genetic algorithm specifically tailored for its resolution. To validate the effectiveness of our proposed approach, we conduct a series of experiments and apply it to real-world scenarios. Our evaluation and comparative analyses unequivocally demonstrate the high efficiency of our method in minimizing energy consumption.
|
|
10:40-11:00, Paper FrA04.3 | |
>On Integrated Optimal Task and Motion Planning for a Tractor-Trailer Rearrangement Problem |
|
Hellander, Anja | Linköping University |
Bergman, Kristoffer | Linköping University |
Axehill, Daniel | Linköping University |
Keywords: Autonomous vehicles, Optimal control, Optimization algorithms
Abstract: In this work, a combined task and motion planner for a tractor and a set of trailers is proposed and it is shown that it is resolution complete and resolution optimal. The proposed planner consists of a task planner and a motion planner that are both based on heuristically guided graph-search. As a step towards tighter integration of task and motion planning, we use the same heuristic that is used by the motion planner in the task planner as well. We further propose to use the motion planner heuristic to give an initial underestimate of the motion costs that are used as costs during the task planning search, and increase this estimate gradually by using the motion planner to verify the cost and feasibility of actions along paths of interest. To limit the time spent in the motion planner, the use of time and cost limits to pause or prematurely abort the motion planner is proposed, which does not affect the resolution completeness or resolution optimality. The planner is evaluated on numerical examples and the results show that the proposed planner can significantly reduce the execution time compared to a baseline resolution optimal task and motion planner.
|
|
11:00-11:20, Paper FrA04.4 | |
>Interaction-Aware Trajectory Prediction and Planning in Dense Highway Traffic Using Distributed Model Predictive Control |
|
Börve, Erik | Chalmers University of Technology |
Murgovski, Nikolce | Chalmers University of Technology |
Laine, Leo | Chalmers |
Keywords: Autonomous vehicles, Optimal control, Predictive control for nonlinear systems
Abstract: In this paper we treat optimal trajectory planning for an autonomous vehicle (AV) operating in dense traffic, where vehicles closely interact with each other. To tackle this problem, we present a novel framework that couples trajectory prediction and planning in multi-agent environments, using distributed model predictive control. A demonstration of our framework is presented in simulation, employing a trajectory planner using non-linear model predictive control. We analyze performance and convergence of our framework, subject to different prediction errors. The results indicate that the obtained locally optimal solutions are improved, compared with decoupled prediction and planning.
|
|
11:20-11:40, Paper FrA04.5 | |
>Model Predictive Control with Collision Avoidance for Unknown Environment |
|
Silvestre, Daniel | NOVA University of Lisbon |
Ramos, Guilherme | Instituto De Telecomunicações, 1049-001 Lisbon, Portugal |
Keywords: Autonomous vehicles, Predictive control for linear systems
Abstract: This paper proposes a model predictive control framework to design autonomous rendezvous operations for terrestrial and space missions in the scope of spacecraft and drones, in the presence of obstacles in an unknown environment. Vehicles equipped with a LiDAR collecting points associated with the obstacles are considered. By proposing an efficient method to compute the smallest ellipse that contains the collected LiDAR points, this work is able to correct, in run time, the vehicle trajectory to avoid collision and reach the rendezvous target. Finally, simulations of the proposed approach to show its effectiveness are presented.
|
|
11:40-12:00, Paper FrA04.6 | |
>Perception-Aware Trajectory Planning for a Pair of Unicycle-Like Robots with Absolute and Relative Ranging Measurements |
|
Riz, Francesco | University of Trento |
Palopoli, Luigi | University of Trento |
Fontanelli, Daniele | University of Trento |
Keywords: Nonholonomic systems, Autonomous vehicles, Robotics
Abstract: We consider two ``kidnapped'' unicycle vehicles released in an unknown environment. Each one is in sight of a ranging sensor (anchor) and has to choose a trajectory that enables it to localise itself relying only on its anchor measurements, on its odometry and on the information (state and mutual distance) that it can exchange with the other vehicle when they are sufficiently close. We propose a motion planning algorithm that solves the simultaneous localisation problem in this challenging scenario.
|
|
FrA05 |
Simpor Junior 4912 |
Policy Optimization Methods and Data-Driven Learning-Based Control |
Invited Session |
Chair: Tang, Yujie | Peking University |
Co-Chair: You, Keyou | Tsinghua University |
Organizer: Tang, Yujie | Peking University |
Organizer: You, Keyou | Tsinghua University |
|
10:00-10:20, Paper FrA05.1 | |
>Learning to Control under Communication Constraints |
|
Aggarwal, Shubham | University of Illinois, Urbana Champaign |
Velicheti, Raj Kiriti | University of Illinois at Urbana Champaign |
Basar, Tamer | Univ of Illinois, Urbana-Champaign |
Keywords: Networked control systems, Optimization, Constrained control
Abstract: How to effectively communicate over wireless networks characterized by link failures is central to understanding the fundamental limits in the performance of a networked control system. In this paper, we study the online remote control of linear-quadratic Gaussian systems over unreliable wireless channels (with random packet drops), where the controller is a priori oblivious to the cost parameters. We first reformulate the problem using a semi-definite program and consequently compute a stabilizing policy from its solution. We then derive a O(sqrt(T)) regret bound (against a best offline policy in hindsight) for a projected online gradient algorithm, where T is the length of the horizon of interest. In the process, we introduce finite time notions of the classical mean-square stability, which may be of independent interest. Finally, we provide a numerical example to validate the theoretical results, demonstrating the limitations induced by lossy communication on the control performance.
|
|
10:20-10:40, Paper FrA05.2 | |
>On the Global Optimality of Direct Policy Search for Nonsmooth H∞ Output-Feedback Control (I) |
|
Tang, Yujie | Peking University |
Zheng, Yang | University of California San Diego |
Keywords: Optimization, Robust control, Optimal control
Abstract: Direct policy search has achieved great empirical success in reinforcement learning. Recently, there has been increasing interest in studying its theoretical properties for continuous control, and fruitful results have been established for linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) control that are smooth and nonconvex. In this paper, we consider the standard H∞ robust control for output feedback systems and investigate the global optimality of direct policy search. Unlike LQR or LQG, the H∞ cost function is nonsmooth in the policy space. Despite the lack of smoothness and convexity, our main result shows that for a class of non-degenerate stabilizing controllers, all Clarke stationary points of H∞ robust control are globally optimal and there is no spurious local minimum. Our proof technique is motivated by the idea of differentiable convex liftings (DCL), and we extend DCL to analyze the nonsmooth and nonconvex H∞ robust control via convex reformulation. Our result sheds some light on the analysis of direct policy search for solving nonsmooth and nonconvex robust control problems.
|
|
10:40-11:00, Paper FrA05.3 | |
>Data-Driven Self-Triggering Mechanism for State Feedback Control |
|
Liu, Wenjie | Beijing Institute of Technology, Beijing, China |
Li, Yifei | Beijing Institute of Technology |
Sun, Jian | Beijing Institute of Technology |
Wang, Gang | Beijing Institute of Technology |
Chen, Jie | Beijing Institute of Technology |
Keywords: Data driven control, Predictive control for linear systems, Networked control systems
Abstract: This paper presents a novel approach for data-driven self-triggered state feedback control of unknown linear systems using noisy data gathered offline. The self-triggering mechanism determines the next triggering time by checking whether the difference between the predicted state and the current state is significant or not. However, when the system matrices are unknown, the challenge lies in characterizing the distance between future states and the current state using only data. To address this, we put forth a data-driven online optimization problem for trajectory prediction by using noisy input-state data. Its optimal solution, together with another unknown parameter that reflects the open-loop divergence rate, is shown sufficient for explicitly quantifying the distance. Moreover, a data-driven set-based over-approximating algorithm using matrix zonotopes is subsequently proposed to upper-bound the {open-loop} divergence rate. Leveraging the optimal solution and the upper bound, a self-triggering mechanism is devised for state feedback control systems, which is proven to ensure input-to-state stability. Numerical examples are presented to validate the effectiveness of the proposed method.
|
|
11:00-11:20, Paper FrA05.4 | |
>Data-Enabled Policy Optimization for the Linear Quadratic Regulator (I) |
|
Zhao, Feiran | Tsinghua University |
Dörfler, Florian | Swiss Federal Institute of Technology (ETH) Zurich |
You, Keyou | Tsinghua University |
Keywords: Learning, Optimization, Sampled-data control
Abstract: Policy optimization (PO), an essential approach of reinforcement learning for a broad range of system classes, requires significantly more system data than indirect (identification-followed-by-control) methods or behavioral-based direct methods even in the simplest linear quadratic regulator (LQR) problem. In this paper, we take an initial step towards bridging this gap by proposing the data-enabled policy optimization (DeePO) method, which requires only a finite number of sufficiently exciting data to iteratively solve the LQR problem via PO. Based on a data-driven closed-loop parameterization, we are able to directly compute the policy gradient from a batch of persistently exciting data. Next, we show that the nonconvex PO problem satisfies a projected gradient dominance property by relating it to an equivalent convex program, leading to the global convergence of DeePO. Moreover, we apply regularization methods to enhance the certainty-equivalence and robustness of the resulting controller and show an implicit regularization property. Finally, we perform simulations to validate our results.
|
|
11:20-11:40, Paper FrA05.5 | |
>Toward Understanding State Representation Learning in MuZero: A Case Study in Linear Quadratic Gaussian Control (I) |
|
Tian, Yi | MIT |
Zhang, Kaiqing | University of Maryland, College Park |
Tedrake, Russ | MIT |
Sra, Suvrit | MIT |
Keywords: Data driven control, Observers for Linear systems, Vision-based control
Abstract: We study the problem of representation learning for control from partial and potentially high-dimensional observations. We approach this problem via direct latent model learning, where one directly learns a dynamical model in some latent state space by predicting costs. In particular, we establish finite-sample guarantees of finding a near-optimal representation function and a near-optimal controller using the directly learned latent model for infinite-horizon time-invariant Linear Quadratic Gaussian (LQG) control. A part of our approach to latent model learning closely resembles MuZero, a recent breakthrough in empirical reinforcement learning, in that it learns latent dynamics implicitly by predicting cumulative costs. A key technical contribution of this work is to prove persistency of excitation for a new stochastic process that arises from our analysis of quadratic regression in our approach.
|
|
11:40-12:00, Paper FrA05.6 | |
>Exact Subspace Diffusion for Decentralized Multitask Learning (I) |
|
Wadehra, Shreya | Imperial College London |
Nassif, Roula | Universite Cote D'Azur |
Vlaski, Stefan | Imperial College London |
Keywords: Learning, Optimization algorithms, Adaptive systems
Abstract: Classical paradigms for distributed learning, such as federated or decentralized gradient descent, employ consensus mechanisms to enforce homogeneity among agents. While these strategies have proven effective in i.i.d. scenarios, they can result in significant performance degradation when agents follow heterogeneous objectives or data. Distributed strategies for multitask learning, on the other hand, induce relationships between agents in a more nuanced manner, and encourage collaboration without enforcing consensus. We develop a generalization of the exact diffusion algorithm for subspace constrained multitask learning over networks, and derive an accurate expression for its mean-squared deviation when utilizing noisy gradient approximations. We verify numerically the accuracy of the predicted performance expressions, as well as the improved performance of the proposed approach over alternatives based on approximate projections.
|
|
FrA06 |
Simpor Junior 4911 |
Estimation and Control of Infinite Dimensional Systems II |
Invited Session |
Chair: Demetriou, Michael A. | Worcester Polytechnic Institute |
Co-Chair: Burns, John A | Virginia Tech |
Organizer: Demetriou, Michael A. | Worcester Polytechnic Institute |
Organizer: Burns, John A | Virginia Tech |
|
10:00-10:20, Paper FrA06.1 | |
>Adaptive Spatial PID and PD Coupling in Synchronization Control of Collocated Infinite and Finite Dimensional Systems (I) |
|
Demetriou, Michael A. | Worcester Polytechnic Institute |
Keywords: Distributed parameter systems
Abstract: This paper presents an entirely different approach for the synchronization of identical networked infinite dimensional systems. With a large class of infinite dimensional systems representing partial differential equations (PDEs), the concept of a functional form of the consensus protocol used for synchronization is applied here and incorporates spatial derivatives and spatial averages of the differences of the PDE states. This leads to spatial PD-type of consensus protocols for synchronization of PDEs. When the networked PDEs are tasked with following a leader, also described by a PDE of the same type, an added component of the controller is incorporated to ensure leader following. The proposed PD-coupling in the synchronization control of infinite dimensional systems attains a new form for the finite dimensional case, where now a temporal PID coupling in the consensus protocol is implemented. Simulation studies for both the infinite and the finite dimensional cases are included to demonstrate the effects of the non-traditional coupling in the synchronization control of networked systems.
|
|
10:20-10:40, Paper FrA06.2 | |
>Consensus of Networked Hyperbolic Systems Via Event-Triggered Boundary Feedback Control (I) |
|
Lu, Mengyao | Beijing University of Technology |
Zhan, Jingyuan | Beijing University of Technology |
Zhang, Liguo | Beijing University of Technology |
Keywords: Distributed parameter systems, Cooperative control, Traffic control
Abstract: This paper investigates the consensus problem of networked hyperbolic partial differential equation (PDE) systems for reaching an agreement over the whole spatial domain via event-triggered boundary feedback control. Consensus controllers are proposed for each PDE system based on the boundary information of its neighboring systems, where both centralized and distributed event-triggered strategies are designed in order to reduce the controller updating frequency. By employing the Lyapunov technique, sufficient conditions with respect to system matrices, event-triggered conditions and the undirected communication topology are obtained to ensure consensus of the networked systems, and it is proved that the Zeno behavior can also be avoided. Finally, the consensus control of a three-lane freeway traffic flow system modeled by Aw-Rascle-Zhang Equations is given as an application example, and the numerical simulation is carried out to validate the theoretical results.
|
|
10:40-11:00, Paper FrA06.3 | |
>Stabilization by 1D Boundary Actuation of Distal 1D Reaction-Diffusion PDE through Heat PDE on a Rectangle (I) |
|
Guan, Dandan | Donghua University |
Qi, Jie | Donghua University |
Krstic, Miroslav | University of California, San Diego |
Keywords: Backstepping, Distributed parameter systems
Abstract: This paper presents a backstepping control design method of stabilization unstable 1D reaction-diffusion system, where the input is a 1D function on an edge of a rectangle, the distal system is a 1D reaction-diffusion PDE on the opposite edge of the rectangle, and the actuator dynamics in between are a 2D heat PDE on the rectangle between the opposite edges. A novel invertible integral transformation is introduced and the resulting controller with feedback of both PDEs' states (the distal 1D and the interior 2D states). We define a new Lyapunov function that contains cosine coefficients to prove the exponential stability in H^2 norm of the closed-loop system. Finally, the theoretical result is illustrated by simulations on a numerical example.
|
|
11:00-11:20, Paper FrA06.4 | |
>Stability of Linear KdV Equation in a Network with Bounded and Unbounded Lengths (I) |
|
Parada, Hugo | Université Grenoble Alpes, Laboratoire Jean Kunzmann |
Crépeau, Emmanuelle | Université De Versailles Saint Quentin |
Prieur, Christophe | CNRS |
Keywords: Distributed parameter systems, Stability of linear systems, Network analysis and control
Abstract: In this work, we study the exponential stability of a system of linear Korteweg-de Vries (KdV) equations interconnected through the boundary conditions on a star-shaped network structure. On each branch of the network, we define a linear KdV equation defined on a bounded domain (0,ℓj) or the half-line (0,∞). We start by proving well-posedness using semigroup theory and then some hidden regularity results. Then, we state the exponential stability of the linear KdV equation by acting with a damping term on not all the branches. This is proved by using compactness argument deriving a suitable observability inequality.
|
|
11:20-11:40, Paper FrA06.5 | |
>Pressure Stabilized POD Reduced Order Model for Control of Viscous Incompressible Flows (I) |
|
Ravindran, S.S. | University of Alabama in Huntsville |
Keywords: Reduced order modeling, Computational methods, Fluid flow systems
Abstract: In this paper, we propose a new pressure-stabilized proper orthogonal decomposition reduced order model (POD- ROM) for the control of viscous incompressible flows. It is a velocity-pressure ROM that uses pressure modes as well to compute the reduced order pressure needed for instance in the control drag and lift forces on bodies in the flow. We also propose and analyze a decoupled time-stepping scheme that uncouples the computation of velocity and pressure variables. It allows us at each time step to solve linear problems, uncoupled in pressure and velocity, which can greatly improve computational efficiency. Numerical studies are performed to discuss the accuracy and performance of the new pressure- stabilized ROM in the simulation of control of flow past a forward-facing step channel
|
|
11:40-12:00, Paper FrA06.6 | |
>Delta-Method Induced Confidence Bands for a Parameter-Dependent Evolution System with Application to Transdermal Alcohol Concentration Monitoring (I) |
|
Liu, Haoxing | University of Southern California |
Goldstein, Larry | University of Southern California |
Luczak, Susan | University of Southern California |
Rosen, I. Gary | Univ. of Southern California |
Keywords: Estimation, Distributed parameter systems, Healthcare and medical systems
Abstract: Uncertainty caused by parameter randomness in a system modeling the relationship between alcohol concentration level in the blood (BAC) or breath (BrAC) and transdermal alcohol concentration (TAC) measured on the surface of the skin by a wearable, non-invasive, electro-chemical biosensor is considered. The parameter-dependent impulse response function (IRF) and system output in the form of a convolution are expressed in terms of an analytic semigroup of operators with regularly dissipative generator set in a Gelfand triple of Hilbert spaces. The Fr'echet derivative of the analytic semigroup in this setting is used to study the variation in the response function resulting from the uncertainties in the parameters described by probability distributions whose statistics depend on regression models with covariates as predictor variables. Finite dimensional approximation of the infinite dimensional state space system and the multi-variate delta method for nonlinear functions of random vectors with asymptotically normal distributions are used to obtain approximating uniform confidence bands for the IRF and the TAC output signal. Convergence of the approximations and three different techniques for obtaining the confidence bands are analyzed and compared.
|
|
FrA07 |
Simpor Junior 4813 |
Identification, Optimization, and Games for Stochastic Systems |
Invited Session |
Chair: Zhao, Wenxiao | Academy of Mathematics and Systems Science, Chinese Academy of Sciences |
Co-Chair: Mu, Biqiang | Chinese Academy of Sciences |
Organizer: Zhao, Wenxiao | Academy of Mathematics and Systems Science, Chinese Academy of Sciences |
Organizer: Qi, Hongsheng | AMSS, Chinese Academy of Sciences |
Organizer: Mu, Biqiang | Chinese Academy of Sciences |
|
10:00-10:20, Paper FrA07.1 | |
>Sparse Plus Low-Rank Identification of Latent-Variable Graphical ARMA Models (I) |
|
You, Junyao | Beijing Institute of Technology |
Yu, Chengpu | Beijing Institute of Technology |
Keywords: Identification, Estimation
Abstract: This paper deals with the identification of graphical autoregressive moving-average (ARMA) models with latent variables. Combining sparse structural characteristics of the graphical model with low-rank modeling of the latent variables, a sparse plus low-rank based iterative identification algorithm is proposed. The topological information embedded in the sparse AR dynamics is estimated from a regularized Yule-Walker optimization problem, which is then treated as prior graphical structure constraint. The latent-variable plus MA part is identified by solving a convex constrained trace norm minimization problem. Based on the MA part estimate and the structural constraint, the graphical AR estimates are updated by the sparse plus low-rank optimization framework and are then used for the update of the latent-variable plus MA part. The effectiveness of the proposed method is illustrated through a simulation study.
|
|
10:20-10:40, Paper FrA07.2 | |
>An Efficient Implementation for Bayesian Manifold Regularization Method (I) |
|
Zhang, Junpeng | The Chinese University of Hong Kong, Shenzhen |
Ju, Yue | KTH Royal Institute of Technology |
Wahlberg, Bo | KTH Royal Institute of Technology |
Mu, Biqiang | Chinese Academy of Sciences |
Chen, Tianshi | The Chinese University of Hong Kong, Shenzhen, China |
Keywords: Identification, Estimation, Computational methods
Abstract: When applying the Bayesian manifold regularization method to function estimation problem with manifold constraints, the direct implementation has computational complexity mathcal{O}(N^3), where N is the number of input-output data measurements. This becomes particularly costly when N is large. In this paper, we propose a more efficient implementation based on the Kalman filter and smoother using a state-space model realization of the underlying Gaussian process. Moreover, we explore the sequentially semi-separable structure of the Laplacian matrix and the posterior covariance matrix. Our proposed implementation has computational complexity mathcal{O}(N) and thus can be applied to large data problems. We exemplify the effectiveness of our proposed implementation through numerical simulations.
|
|
10:40-11:00, Paper FrA07.3 | |
>New Approach to Variable Selection for Nonparametric Nonlinear Systems (I) |
|
Ren, Xiaotao | Key Laboratory of Systems and Control, Academy of Mathematics An |
Zhao, Wenxiao | Academy of Mathematics and Systems Science, Chinese Academy of S |
Gao, Jinwu | Jilin University |
Keywords: Nonlinear systems identification
Abstract: Let the observation be generated by the nonlinear ARX (NARX) systems. A new method for variable selection of the nonlinear function within the system at any interested points is introduced. In contrast to most of the existing results, the new method is not based on optimizing a certain criterion, and estimates from the variable selection algorithm given in this paper are easy to update computationally in comparison with the criterion-optimization-based methods when new data arrive. Under reasonable conditions the estimates are proved to converge to the true contributing variables with probability one.
|
|
11:00-11:20, Paper FrA07.4 | |
>A Family of Hyper-Parameter Estimators for Regularized Linear System Identification (I) |
|
Zhang, Meng | Academy of Mathematics and System Science, Chinese Academy of Sc |
Chen, Tianshi | The Chinese University of Hong Kong, Shenzhen, China |
Mu, Biqiang | Chinese Academy of Sciences |
Keywords: Identification, Linear systems
Abstract: Hyper-parameter estimation is one of the fundamental issues for kernel-based regularized system identification methods. Empirical Bayes (EB) estimator and Stein's unbiased risk estimator (SURE) are two popular hyper-parameter estimators, but they both have advantages and disadvantages. Specifically, EB is not asymptotically optimal in the mean squared error (MSE) sense but SURE is, while SURE is more sensitive to ill-conditioned regression matrices but EB is more robust. In this paper, to find a better estimator by combining their strength and mitigating their weakness, we propose a family of hyper-parameter estimators by linking EB and SURE estimators together through an index. The finite sample and asymptotic properties of this family of estimators have been established. The Monte Carlo simulation results show that there does exist a ``middle" hyper-parameter estimator in this family that is superior to the EB and SURE.
|
|
11:20-11:40, Paper FrA07.5 | |
>Multi-Agent Deep Reinforcement Learning for Large-Scale Platoon Coordination with Partial Information at Hubs (I) |
|
Wei, Dixiao | Tongji University |
Yi, Peng | Tongji University |
Lei, Jinlong | Tongji University |
Keywords: Machine learning, Agents-based systems, Traffic control
Abstract: This paper considers the hub-based platoon coordination problem in the large-scale transportation network, to promote cooperation among trucks and optimize the overall efficiency of the transportation network. We design a distributed communication model for transportation networks and transform the problem into a Dec-POMDP (Decentralized-Partial Observable Markov Decision Process). We then propose the A-QMIX deep reinforcement learning algorithm to solve the problem, which adopts centralized training and distributed execution and hence provides a reliable model for trucks to make quick decisions using only partial information. Finally, we carry out experiments with 100 and 1000 trucks in the transportation network of the Yangtze River Delta region in China to demonstrate the effectiveness and real-time performance of the proposed algorithm.
|
|
11:40-12:00, Paper FrA07.6 | |
>Compressibility of Voter-Model State Snapshots in the Graph Spectral Basis (I) |
|
Zhu, Chenyan | Texas A&M University |
Roy, Sandip | Washington State University |
Keywords: Network analysis and control, Stochastic systems, Control of networks
Abstract: The sparsity or compressibility of network spread states in a graph-spectrum basis is examined, in the context of a stochastic model for influence/spread known as the voter model. In particular, first- and second- moments are characterized, for the graph-spectrum basis components contained in the voter-model state. These formal characterizations, as well as an asymptotic analysis of the voter model, are used to relate compressibility with the network's graph. An illustrative example as well as a simulation of a larger-scale model are included.
|
|
FrA08 |
Simpor Junior 4812 |
Optimal Control VII |
Regular Session |
Chair: Khani, Alireza | University of Minnesota-Twin Cities |
Co-Chair: Shvartsman, Ilya | Penn State Harrisburg |
|
10:00-10:20, Paper FrA08.1 | |
>Near-Optimal Control of Nonlinear Systems with Hybrid Inputs and Dwell-Time Constraints |
|
Lal-Fediuc, Ioana | Technical University of Cluj-Napoca |
Morarescu, Irinel-Constantin | CRAN, CNRS, Université De Lorraine |
Daafouz, Jamal | Université De Lorraine, CRAN, CNRS |
Busoniu, Lucian | Technical University of Cluj-Napoca |
Keywords: Optimal control, Switched systems, Numerical algorithms
Abstract: We propose two new optimistic planning algorithms for nonlinear hybrid-input systems, in which the input has both a continuous and a discrete component, and the discrete component must respect a dwell-time constraint. Both algorithms select sets of input sequences for refinement at each step, along with a continuous or discrete step to refine (split). The dwell-time constraint means that the discrete splits must keep the discrete mode constant if the required dwell-time is not yet reached. Convergence rate guarantees are provided for both algorithms, which show the dependency between the near-optimality of the sequence returned and the computational budget. The rates depend on a novel complexity measure of the dwell-time constrained problem. We present simulation results for two problems, an adaptive-quantization networked control system and a model for the COVID pandemic.
|
|
10:20-10:40, Paper FrA08.2 | |
>Continuous Optimization for Control of Finite-State Machines with Cascaded Hysteresis Via Time-Freezing |
|
Van Roy, Wim | KU Leuven |
Nurkanovic, Armin | University of Freiburg |
Abbasi Esfeden, Ramin | KU Leuven |
Frey, Jonathan | University of Freiburg |
Pozharskiy, Anton | University of Freiburg |
Swevers, Jan | K. U. Leuven |
Diehl, Moritz | University of Freiburg |
Keywords: Optimal control, Switched systems, Optimization
Abstract: Control problems with Finite-State Machines (FSM) are often solved using integer variables, leading to a mixed-integer optimal control problem (MIOCP). This paper proposes an alternative method to describe a subclass of FSMs using complementarity constraints and time-freezing. The FSM from this subclass is built up by a sequence of states where a transition between the states is triggered by a single switching function. This can be looked at as a cascade of hysteresis loops where a memory effect is used to maintain the active state of the state machine. Based on the reformulation for hybrid systems with a hysteresis loop, a method is developed to reformulate this subclass in a similar fashion. The approach transforms the original problem into a Piecewise Smooth System (PSS), which can be discretized using the recently developed Finite Elements with Switch Detection, allowing for high-accuracy solutions. The reformulation is compared to a mixed-integer formulation from the literature on a time-optimal control problem. This work is a first step towards the general reformulation of FSMs into nonsmooth systems without integer states.
|
|
10:40-11:00, Paper FrA08.3 | |
>Convexification of Robust Trajectory Planning Problems with Nominal State and Control Dependent Uncertainties |
|
Sheridan, Oliver | University of Washington |
Acikmese, Behcet | University of Washington |
Keywords: Optimal control, Uncertain systems, Aerospace
Abstract: We consider the problem of robust trajectory optimization of constrained discrete-time linear systems under bounded uncertainty. This paper extends our previous work on robust trajectory planning for linear systems with control-dependent uncertainties to a more general class of uncertainties, including nominal-state-dependent uncertainties. In particular, we show that if strong duality holds for the robust state constraints, and if the uncertainties are bounded by convex elementwise nonnegative functions of the nominal state and control, the robust constraints can be equivalently reformulated as deterministic convex constraints, enabling globally optimal solutions with no conservatism. We first use convex duality theory to reformulate robust linear inequality state constraints as deterministic biconvex constraints . We then exploit the elementwise nonnegativity of the uncertainty bounds to remove the biconvexity in closed form, resulting in convex deterministic constraints that can be handled by off-the-shelf solvers. These two lemmas are our main contribution, and lead to our final result, and equivalent convex reformulation of the original robust optimization problem which allows efficient trajectory optimization solutions under control and state dependent uncertainties. We then demonstrate the practical applicability of our method via numerical simulations.
|
|
11:00-11:20, Paper FrA08.4 | |
>Optimality Conditions in Infinite-Horizon Optimal Control Problem with Vanishing Discounting |
|
Shvartsman, Ilya | Penn State Harrisburg |
Keywords: Optimal control
Abstract: We consider an optimal control problem on infinite horizon with a vanishing discounting factor, state sufficient conditions of optimality and illustrate them with examples.
|
|
11:20-11:40, Paper FrA08.5 | |
>Efficient and Real-Time Reinforcement Learning for Linear Quadratic Systems with Application to H-Infinity Control |
|
Aalipour, Ali | University of Minnesota |
Khani, Alireza | University of Minnesota-Twin Cities |
Keywords: Optimal control, Iterative learning control, Linear systems
Abstract: This paper presents a model-free, real-time, data-efficient Q-learning-based algorithm to solve the H_{infty} control of linear discrete-time systems. The computational complexity is shown to reduce from mathcal{O}(underline{q}^3) in the literature to mathcal{O}(underline{q}^2) in the proposed algorithm, where underline{q} is quadratic in the sum of the size of state variables, control inputs, and disturbance. An adaptive optimal controller is designed and the parameters of the action and critic networks are learned online without the knowledge of the system dynamics, making the proposed algorithm completely model-free. Also, a sufficient probing noise is only needed in the first iteration and does not affect the proposed algorithm. With no need for an initial stabilizing policy, the algorithm converges to the closed-form solution obtained by solving the Riccati equation. A simulation study is performed by applying the proposed algorithm to real-time control of an autonomous mobility-on-demand (AMoD) system for a real-world case study to evaluate the effectiveness of the proposed algorithm.
|
|
11:40-12:00, Paper FrA08.6 | |
>Open-Loop and Feedback LQ Potential Differential Games for Multi-Agent Systems |
|
Scarpa, Maria Luisa | Imperial College London |
Mylvaganam, Thulasi | Imperial College London |
Keywords: Optimal control, Game theory, Linear systems
Abstract: Open-loop and feedback potential differential games for multi-agent systems are considered in this paper. Constructive sufficient conditions under which a linear quadratic differential game constitutes a potential differential game are provided. The conditions enable the construction of associated optimal control problems that yield (at significantly reduced computational complexity) solutions (in terms of open-loop and feedback Nash equilibrium strategies) of the original differential game. The results are demonstrated on a practically-motivated example that concerns spacecraft formation control.
|
|
FrA09 |
Simpor Junior 4811 |
Optimization II |
Regular Session |
Chair: Jiang, Wei | Aalto University, Finland |
Co-Chair: Charalambous, Themistoklis | University of Cyprus |
|
10:00-10:20, Paper FrA09.1 | |
>Distributed Markov Chain-Based Strategies for Multi-Agent Robotic Surveillance |
|
Diaz-Garcia, Gilberto | University of California, Santa Barbara |
Bullo, Francesco | Univ of California at Santa Barbara |
Marden, Jason R. | University of California, Santa Barbara |
Keywords: Optimization, Markov processes, Robotics
Abstract: Markov chains have been increasingly used to define persistent robotic surveillance schemes. Motivations for this design choice include their easy implementation, unpredictable surveillance patterns, and their well-studied mathematical background. However, applying previous results to scenarios with multiple agents can significantly increase the dimension of the problem, leading to intractable algorithms. In this work we analyze the hitting time minimization problem for multiple agents moving over a finite graph. We exploit the structure of this problem to propose a tractable algorithm to design Markov chains to cover the graph with multiple interacting agents. Using mathematical analysis, we provide guarantees for the convergence of our proposed solution. Also, through numerical simulations, we show the performance of our approach compared to the current state of art in multi-agent scenarios.
|
|
10:20-10:40, Paper FrA09.2 | |
>A Unified Early Termination Technique for Primal-Dual Algorithms in Mixed Integer Conic Programming |
|
Chen, Yuwen | University of Oxford |
Ning, Catherine | University of Oxford |
Goulart, Paul J. | University of Oxford |
Keywords: Optimization, Numerical algorithms, Optimal control
Abstract: We propose an early termination technique for mixed integer conic programming for use within branch-and-bound based solvers. Our approach generalizes previous early termination results for ADMM-based solvers to a broader class of primal-dual algorithms, including both operator splitting methods and interior point methods. The complexity for checking early termination is O(n) for each termination check assuming a bounded problem domain. We show that this domain restriction can be relaxed for problems whose data satisfies a simple rank condition, in which case each check requires an O(n^2) solve using a linear system that must be factored only once at the root node. We further show how this approach can be used in hybrid model predictive control as long as system inputs are bounded. Numerical results show that our method leads to a moderate reduction in the total iterations required for branch-and-bound conic solvers with interior-point based subsolvers.
|
|
10:40-11:00, Paper FrA09.3 | |
>Global Resolution of Chance-Constrained Optimization Problems: Minkowski Functionals and Monotone Inclusions |
|
Zhang, Peixuan | Pennsylvania State University |
Shanbhag, Uday V. | Pennsylvania State University |
Lagoa, Constantino M. | Pennsylvania State Univ |
Bardakci, Ibrahim Ekrem | Bartin University |
Keywords: Optimization, Numerical algorithms, Uncertain systems
Abstract: Chance-constrained optimization problems are generally complicated by uncertainty, nonsmoothness, and nonconvexity. Yet, non-asymptoic rates and complexity guarantees for computing an epsilon-global minimizer remain open questions. We consider a subclass of problems in which the probability is defined as mathbb{P}left{ zeta mid zeta in K(x) right}, K(x) is a set defined as K(x) , = , { zeta in Kscr , mid , c(x,zeta) leq 1} where c(x,bullet) is a positively homogenous function for any x in Xscr and Kscr is a nonempty, compact, and convex set, symmetric about the origin. We make two contributions in this context. (i) First, when zeta admits a log-concave density on Kscr, the chance-constrained formulation admits an equivalent convex representation and under a suitable regularity condition, the necessary and sufficient conditions are captured by a monotone inclusion with a compositional expectation-valed operator. (ii) Second, when zeta admits a uniform density, we present a variance-reduced stochastic proximal-point framework for resolving the monotone inclusion and provide amongst the first rate and complexity guarantees for such a problem.
|
|
11:00-11:20, Paper FrA09.4 | |
>Variational Principles for Mirror Descent and Mirror Langevin Dynamics |
|
Tzen, Belinda | Columbia University |
Raj, Anant | INRIA - Ecole Normale Supérieure |
Raginsky, Maxim | University of Illinois at Urbana-Champaign |
Bach, Francis | INRIA - Ecole Normale Supérieure |
Keywords: Optimization, Optimal control, Stochastic optimal control
Abstract: Mirror descent, introduced by Nemirovski and Yudin in the 1970s, is a primal-dual convex optimization method that can be tailored to the geometry of the optimization problem at hand through the choice of a strongly convex potential function. It arises as a basic primitive in a variety of applications, including large-scale optimization, machine learning, and control. This paper proposes a variational formulation of mirror descent and of its stochastic variant, mirror Langevin dynamics. The main idea, inspired by the classic work of Brezis and Ekeland on variational principles for gradient flows, is to show that mirror descent emerges as a closed-loop solution for a certain optimal control problem, and the Bellman value function is given by the Bregman divergence between the initial condition and the global minimizer of the objective function.
|
|
11:20-11:40, Paper FrA09.5 | |
>Leveraging Proximal Optimization for Differentiating Optimal Control Solvers |
|
Bounou, Oumayma | Inria, ENS |
Ponce, Jean | Ecole Normale Supérieure |
Carpentier, Justin | Inria |
Keywords: Optimization, Optimal control, Learning
Abstract: Over the past few years, differentiable optimization has gained interest within machine learning, control, and robotics communities. It consists in computing the derivatives of the solutions of a given optimization problem which can then be used in learning algorithms. Until now, dedicated approaches have been proposed to compute the derivatives of various optimization problems (LPs, QPs, SOCPs, etc.). However, these approaches assume the problems are well-conditioned, limiting textit{de facto} their application to general optimal control problems (OCP) widely used in robotics. In this work, we focus on the differentiation of such problems. We notably introduce a differentiable proximal formulation of equality-constrained LQR problems that accurately solves rank-deficient problems. This proximal formulation allows us to compute accurate gradients even in the case of problems that do not satisfy the standard linear independence constraint qualification (LICQ). Because any optimal control problem can be cast as an equality-constrained LQR problem in the vicinity of the optimal solution, we show that our robust LQR derivatives computation can be exploited to obtain the derivatives of general optimal control problems. We demonstrate the effectiveness of our approach in dynamics learning and parameter identification experiments in both linear and nonlinear optimal control problems.
|
|
11:40-12:00, Paper FrA09.6 | |
>Distributed Optimization Via Gradient Descent with Event-Triggered Zooming Over Quantized Communication |
|
Rikos, Apostolos I. | KTH Royal Institute of Technology |
Jiang, Wei | Aalto University, Finland |
Charalambous, Themistoklis | University of Cyprus |
Johansson, Karl H. | KTH Royal Institute of Technology |
Keywords: Optimization, Optimization algorithms, Agents-based systems
Abstract: In this paper, we study unconstrained distributed optimization strongly convex problems, in which the exchange of information in the network is captured by a directed graph topology over digital channels that have limited capacity (and hence information should be quantized). Distributed methods in which nodes use quantized communication yield a solution at the proximity of the optimal solution, hence reaching an error floor that depends on the quantization level used; the finer the quantization the lower the error floor. However, it is not possible to determine in advance the optimal quantization level that ensures specific performance guarantees (such as achieving an error floor below a predefined threshold). Choosing a very small quantization level that would guarantee the desired performance, requires information packets of very large size, which is not desirable (could increase the probability of packet losses, increase delays, etc) and often not feasible due to the limited capacity of the channels available. In order to obtain a communication-efficient distributed solution and a sufficiently close proximity to the optimal solution, we propose a quantized distributed optimization algorithm that converges in a finite number of steps and is able to adjust the quantization level accordingly. The proposed solution uses a finite-time distributed optimization protocol to find a solution to the problem for a given quantization level in a finite number of steps and keeps refining the quantization level until the difference in the solution between two successive solutions with different quantization levels is below a certain pre-specified threshold. Therefore, the proposed algorithm progressively refines the quantization level, thus eventually achieving low error floor with a reduced communication burden. The performance gains of the proposed algorithm are demonstrated via illustrative examples.
|
|
FrA10 |
Roselle Junior 4713 |
Neural Networks II |
Regular Session |
Chair: Raginsky, Maxim | University of Illinois at Urbana-Champaign |
Co-Chair: Tóth, Roland | Eindhoven University of Technology |
|
10:00-10:20, Paper FrA10.1 | |
>Gasoline Controlled Auto-Ignition with Learning-Based Uncertainty Using Stochastic Model Predictive Control |
|
Chen, Xu | RWTH Aachen University |
Basler, Maximilian | RWTH Aachen University |
Ketelhut, Maike | RWTH Aachen University |
Abel, Dirk | RWTH Aachen University |
Keywords: Neural networks, Predictive control for linear systems, Control applications
Abstract: The internal combustion engine faces a severe energy conservation and emission reduction challenge. In this regard, low-temperature combustion technology is a profitable solution, allowing for pollutant emission reduction while improving engine efficiency. However, the process is complex, and the cycles are mutually coupled, making it a huge challenge to stabilize the entire process behavior. Also, the model mismatch and the inherent stochasticity of the process bring considerable difficulties to the application of control technology. In this work, we propose a deep learning-based generative model to learn the distribution of system uncertainties. The uncertainty information is considered in the model predictive control (MPC) strategy design. We adopt the disturbance-affine stochastic MPC (sMPC) and transform the chance-constrained MPC problem into some tractable optimization problems. The results show better closed-loop performance with smaller output variance, given the prior knowledge of uncertainty realization from the proposed generative model.
|
|
10:20-10:40, Paper FrA10.2 | |
>Computationally Efficient Predictive Control Based on ANN State-Space Models |
|
Hoekstra, Jan Hidde | Eindhoven University of Technology |
Cseppentő, Bence | Budapest University of Technology and Economics |
Beintema, Gerben Izaak | Eindhoven University of Technology |
Schoukens, Maarten | Eindhoven University of Technology |
Kollar, Zsolt | Budapest University of Technology and Economics |
Tóth, Roland | Eindhoven University of Technology |
Keywords: Neural networks, Predictive control for nonlinear systems, Linear parameter-varying systems
Abstract: Artificial neural networks (ANN) have been shown to be flexible and effective function estimators for the identification of nonlinear state-space models. However, if the resulting models are used directly for nonlinear model predictive control (NMPC), the resulting nonlinear optimization problem is often overly complex due to the size of the network, requires the use of high-order observers to track the states of the ANN model, and the overall control scheme does not exploit the available autograd tools for these models. In this paper, we propose an efficient approach to auto-convert ANN state-space models to linear parameter-varying (LPV) form and solve predictive control problems by successive solutions of linear model predictive problems, corresponding to quadratic programs (QPs). Furthermore, we show how existing deep-learning methods, such as SUBNET that uses a state encoder, enable efficient implementation of MPCs on identified ANN models. Performance of the proposed approach is demonstrated by a simulation study on an unbalanced disc system.
|
|
10:40-11:00, Paper FrA10.3 | |
>An Analytic End-To-End Deep Learning Algorithm Based on Collaborative Learning |
|
Li, Sitan | Nanyang Technological University |
Cheah, Chien Chern | Nanyang Tech. Univ |
Keywords: Neural networks, Robotics, Lyapunov methods
Abstract: In most control applications, theoretical analysis of the systems is crucial in ensuring stability or convergence, so as to ensure safe and reliable operations and also to gain a better understanding of the systems for further developments. However, most current deep learning methods are black-box approaches that are more focused on empirical studies. This paper develops an analytic end-to-end learning algorithm for deep fully connected neural networks(FNN). Unlike existing end-to-end deep learning methods, the convergence analysis of the proposed method is assured based on smooth sigmoid activation functions and thus avoiding any potential chattering problem, but the proposed method does not easily lead to gradient vanishing problems. The proposed End-to-End algorithm trains multiple two-layer fully connected networks concurrently and collaborative learning can be used to further combine their strengths to improve accuracy. A classification case study based on fully connected networks and MNIST dataset was done to demonstrate the performance of the proposed approach. Then an online kinematics control task of a UR5e robot arm was performed to illustrate the regression approximation and online updating ability of our algorithm.
|
|
11:00-11:20, Paper FrA10.4 | |
>Tight Certified Robustness Via Min-Max Representations of ReLU Neural Networks |
|
Anderson, Brendon G. | University of California, Berkeley |
Pfrommer, Samuel | University of California, Berkeley |
Sojoudi, Somayeh | UC Berkeley |
Keywords: Neural networks, Robust control, Optimization
Abstract: The reliable deployment of neural networks in control systems requires rigorous robustness guarantees. In this paper, we obtain tight robustness certificates over convex attack sets for min-max representations of ReLU neural networks by developing a convex reformulation of the nonconvex certification problem. This is done by "lifting" the problem to an infinite-dimensional optimization over probability measures, leveraging recent results in distributionally robust optimization to solve for an optimal discrete distribution, and proving that solutions of the original nonconvex problem are generated by the discrete distribution under mild boundedness, nonredundancy, and Slater conditions. As a consequence, optimal (worst-case) attacks against the model may be solved for exactly. This contrasts prior state-of-the-art that either requires expensive branch-and-bound schemes or loose relaxation techniques. Experiments on robust control and MNIST image classification examples highlight the benefits of our approach.
|
|
11:20-11:40, Paper FrA10.5 | |
>Safety Filter Design for Neural Network Systems Via Convex Optimization |
|
Chen, Shaoru | University of Pennsylvania |
Chee, Kong Yao | University of Pennsylvania |
Matni, Nikolai | University of Pennsylvania |
Hsieh, M. Ani | University of Pennsylvania |
Pappas, George J. | University of Pennsylvania |
Keywords: Neural networks, Robust control, Uncertain systems
Abstract: With the increase in data availability, it has been widely demonstrated that neural networks (NN) can capture complex system dynamics precisely in a data-driven manner. However, the architectural complexity and nonlinearity of the NNs make it challenging to synthesize a provably safe controller. In this work, we propose a novel safety filter that relies on convex optimization to ensure safety for a NN system, subject to additive disturbances that are capable of capturing modeling errors. Our approach leverages tools from NN verification to over-approximate NN dynamics with a set of linear bounds, followed by an application of robust linear MPC to search for controllers that can guarantee robust constraint satisfaction. We demonstrate the efficacy of the proposed framework numerically on a nonlinear pendulum system.
|
|
11:40-12:00, Paper FrA10.6 | |
>A Constructive Approach to Function Realization by Neural Stochastic Differential Equations |
|
Veeravalli, Tanya | University of Illinois, Urbana-Champaign |
Raginsky, Maxim | University of Illinois at Urbana-Champaign |
Keywords: Neural networks, Stochastic systems, Nonlinear systems
Abstract: The problem of function approximation by neural dynamical systems has typically been approached in a top-down manner: Any continuous function can be approximated to an arbitrary accuracy by a sufficiently complex model with a given architecture. This can lead to high-complexity controls which are impractical in applications. In this paper, we take the opposite, constructive approach: We impose various structural restrictions on system dynamics and consequently characterize the class of functions that can be realized by such a system. The systems are implemented as a cascade interconnection of a neural stochastic differential equation (Neural SDE), a deterministic dynamical system, and a readout map. Both probabilistic and geometric (Lie-theoretic) methods are used to characterize the classes of functions realized by such systems.
|
|
FrA11 |
Roselle Junior 4712 |
Large-Scale Systems I |
Regular Session |
Chair: Weyer, Erik | Univ. of Melbourne |
Co-Chair: Ishii, Hideaki | Tokyo Institute of Technology |
|
10:00-10:20, Paper FrA11.1 | |
>An Optimization-Based Network Partitioning Method Considering Local Controllability: Application to Water Distribution Networks |
|
Arastou, Alireza | University of Melbourne |
Wang, Ye | The University of Melbourne |
Weyer, Erik | Univ. of Melbourne |
Keywords: Large-scale systems, Control system architecture, Distributed control
Abstract: Complex networks pose significant challenges for design of control systems. This paper proposes a partitioning method for large-scale networks to be employed for use in decentralized and distributed control. The paper is divided into two parts. In the first part, a new formulation of the partitioning problem considering both computational and communication costs associated with control is established, and the controllability of the subsystems are also taken into account. In the second part, an effective algorithm is developed to find the solution to the network decomposition problem. The proposed approach is illustrated on a water distribution system.
|
|
10:20-10:40, Paper FrA11.2 | |
>Low-Complexity Linear Parameter-Varying Approximations of Incompressible Navier-Stokes Equations for Truncated State-Dependent Riccati Feedback |
|
Heiland, Jan | Max Planck Institute for Dynamics of Complex Technical Systems |
Werner, Steffen W. R. | Virginia Tech |
Keywords: Large-scale systems, Model/Controller reduction, Numerical algorithms
Abstract: Nonlinear feedback design via state-dependent Riccati equations is well established but unfeasible for large-scale systems because of computational costs. If the system can be embedded in the class of linear parameter-varying (LPV) systems with the parameter dependency being affine-linear, then the nonlinear feedback law has a series expansion with constant and precomputable coefficients. In this work, we propose a general method to approximating nonlinear systems such that the series expansion is possible and efficient even for high-dimensional systems. We lay out the application for the stabilization of incompressible Navier-Stokes equations, discuss the numerical solution of the involved matrix valued equations, and confirm the performance of the approach in a numerical example.
|
|
10:40-11:00, Paper FrA11.3 | |
>Conflict-Free Node-To-Robot Scheduling for Lifelong Operation in a Warehouse with Narrow-Corridor Environment |
|
Singh, Sharad Kumar | Addverb Technologies, Noida |
M, Hemantharaj | Addverb Technologies |
Bhattacharya, Sayantani | Addverb Technologies, Noida |
Jha, Manish | Addverb Technologies |
Keywords: Large-scale systems, Robotics, Autonomous robots
Abstract: This paper presents a solution to lifelong Multi-Agent Path Finding (MAPF) problems for long and narrow-corridor environments. In this setting, robots need to navigate conflict-free paths while adapting to new goals. We propose an algorithm called Conflict-Free Node-To-Robot Scheduling (CFNRS), which effectively coordinates the paths of robots on a given graph in a constrained environment. The algorithm assigns nodes of the graph, ensuring no conflicts with other robots. In particular, we introduce a Deadlock-Detection and Resolution mechanism to find and resolve conflicts and ensure conflict-free paths. We have introduced a problem-reduction technique for improved efficiency. The proposed algorithms are evaluated through simulations in narrow-corridor environments and compared to existing state-of-the-art MAPF solvers, demonstrating their validity and effectiveness in ensuring that robots can navigate conflict-free paths.
|
|
11:00-11:20, Paper FrA11.4 | |
>Local Convergence of Multi-Agent Systems towards Rigid Lattices |
|
Giusti, Andrea | University of Naples Federico II |
Coraggio, Marco | Scuola Superiore Meridionale |
di Bernardo, Mario | University of Naples Federico II |
Keywords: Large-scale systems, Stability of nonlinear systems, Autonomous systems
Abstract: Geometric pattern formation is an important emergent behavior in many applications involving large-scale multi-agent systems, such as sensor networks deployment and collective transportation. Attraction/repulsion virtual forces are the most common control approach to achieve such behavior in a distributed and scalable manner. Nevertheless, for most existing solutions only numerical and/or experimental evidence of their convergence is available. Here, we revisit the problem of achieving pattern formation in spaces of any dimension, giving sufficient conditions to prove analytically that under the influence of appropriate virtual forces, a large-scale multi-agent swarming system locally converges towards a stable and robust rigid lattice configuration. Our theoretical results are complemented by exhaustive numerical simulations confirming their effectiveness and estimating the region of asymptotic stability of the rigid lattice configuration.
|
|
11:20-11:40, Paper FrA11.5 | |
>Ensemble Control of a Large Population of Stochastic Oscillators: Periodic–Feedback Control Approach |
|
Ito, Kaito | Tokyo Institute of Technology |
Kume, Haruhiro | Tokyo Institute of Technology |
Ishii, Hideaki | Tokyo Institute of Technology |
Keywords: Large-scale systems, Stochastic systems, Lyapunov methods
Abstract: In this paper, we address the problem of steering the distribution of oscillators all receiving the same control input to a given desired distribution. In a large population limit, the distribution of oscillators can be described by a probability density. Then, our problem can be seen as an ensemble control problem with a constraint on the steady-state density. In particular, we consider the case where oscillators are subjected to stochastic noise. One of the difficulties of this problem is that due to the stochasticity, it is generally impossible to design a control law under which oscillators converge to a target density exactly. To avoid this issue, we first give an alternative target density that is close enough to the original target. The modified target is carefully designed via a periodic input so that the distribution of oscillators can converge to it by an appropriate control strategy. Next, we construct a controller that decreases the Kullback–Leibler divergence between the distribution of oscillators and the modified target combining a periodic input and feedback control. We exhibit some convergence results for our proposed method. The effectiveness of the proposed method is demonstrated by a numerical example.
|
|
11:40-12:00, Paper FrA11.6 | |
>Entropic Model Predictive Optimal Transport for Underactuated Linear Systems |
|
Ito, Kaito | Tokyo Institute of Technology |
Kashima, Kenji | Kyoto University |
Keywords: Optimal control, Large-scale systems, Predictive control for linear systems
Abstract: This paper investigates dynamical optimal transport of underactuated linear systems over an infinite time horizon. In our previous work, we proposed to integrate model predictive control and the celebrated Sinkhorn algorithm to perform efficient dynamical transport of agents. However, the proposed method requires the invertibility of input matrices, which severely limits its applicability. To resolve this issue, we extend the method to (possibly underactuated) controllable linear systems. In addition, we ensure the convergence properties of the method for general controllable linear systems. The effectiveness of the proposed method is demonstrated by a numerical example.
|
|
FrA12 |
Roselle Junior 4711 |
Distributed Control I |
Regular Session |
Chair: Belkhatir, Zehor | University of Southampton |
Co-Chair: Jagtap, Pushpak | Indian Institute of Science |
|
10:00-10:20, Paper FrA12.1 | |
>Distributed Multi-Robot Flocking Based on Acoustic Doppler Effect |
|
Zhou, Yizhi | Geroge Mason University |
Nowzari, Cameron | George Mason University |
Wang, Xuan | George Mason University |
Keywords: Distributed control, Agents-based systems, Autonomous robots
Abstract: This paper aims to design a distributed algorithm based on Doppler effect that allows multiple robots to achieve a consensus on their velocities. Instead of relying on a direct measurement of robots’ exact or relative velocities, which are usually challenging under denied environments (i.e., underwater), the novelty of our approach stems from utilizing the sound frequency as a medium to coordinate velocities among robots. Such a mechanism is achieved by exploiting the Doppler effect and establishing an equivalence between the velocity consensus of the robots and the frequency consensus of the sound they broadcast/receive. To address scalability and interference issues for large-scale systems, our use of the Doppler effect is broadcast-based, unlike most traditional Doppler devices that are reflection-based. Building on this, we develop a fully distributed algorithm for multi-robot flocking for the one-dimensional case, where the only control input for each robot is the sound frequencies it locally receives. The designed controller leads to highly nonlinear system dynamics. We employ a linearization method to theoretically prove the local convergence of the system to the desired equilibrium for velocity consensus. Simulations demonstrate the effectiveness of the proposed approach.
|
|
10:20-10:40, Paper FrA12.2 | |
>Infinite-Dimensional Output-Feedback Bounded Bilinear Control of a Parallel-Flow Heat Exchanger |
|
Mechhoud, Sarah | University of 20 August 1955 Skikda |
Belkhatir, Zehor | University of Southampton |
Keywords: Distributed control, Constrained control, Output regulation
Abstract: In this paper, we consider the problem of output bounded controller design for a parallel-flow heat exchanger described by 2times 2 coupled linear hyperbolic partial differential equations (PDEs) of balance laws. We aim to drive the internal fluid outlet temperature to track a reference trajectory by manipulating the external fluid velocity. Due to physical limitations, this manipulated variable has to be bounded to avoid a laminar regime. Consequently, the control problem becomes bounded and bilinear. Based on the set-invariance concept and the Lyapunov's stability theory, first, we design a bounded state feedback controller. Then, since only boundary measurements are available, we synthesize an output feedback controller, and demonstrate the exponential stability of the closed-loop system. Finally, simulation results are provided to illustrate the performance of the proposed control technique.
|
|
10:40-11:00, Paper FrA12.3 | |
>A Bound on the Existence of the Maximum Jointly Invariant Set of Input-Coupled Systems |
|
Sánchez-Amores, Ana | University of Seville |
Maestre, Jose Maria (Pepe) | University of Seville |
Trodden, Paul | University of Sheffield |
Camacho, Eduardo F. | Univ. of Sevilla |
Keywords: Distributed control, Constrained control, Robust control
Abstract: We present a set-theoretical characterization of a bound on the maximal portion that an agent can cede of its input variable to another agent. By ceding control authority, agents can decompose coupling variables into public and private parts, which is of interest in situations of partial cooperation. In particular, sufficient conditions under which the non-existence of the maximum robust control invariant set is guaranteed are provided, expressed in terms of support functions and the dominant system eigenvalue. Finally, the results are illustrated via stable and unstable example systems with different coupling.
|
|
11:00-11:20, Paper FrA12.4 | |
>Distributed Optimal Solutions for Multiagent Pursuit-Evasion Games |
|
Zhou, Panpan | KTH Royal Institute of Technology |
Chen, Ben M. | Chinese University of Hong Kong |
Keywords: Distributed control, Control applications, Networked control systems
Abstract: In this paper, distributed optimal solutions are designed for networked multiagent pursuit-evasion (MPE) games for capture and formation control. In the games, the pursuers aim to minimize the distance from their target evaders while the evaders attempt to maximize it, and at the same time, all players desire to maintain cohesion with their teammates. The goals of agents are obviously reflected in the obtained optimal control strategies which consist of an attracting term and/or a repelling term. Nash equilibrium is obtained by means of optimal strategies using the solutions of the HJI equations. Furthermore, three scenarios are considered in the MPE game: one-pursuer-one-evader, multiple-pursuer-oneevader, and multiple-pursuer-multiple-evader, where sufficient conditions are given for pursuers in achieving capture or formation control with ultimate zero or bounded errors. It is shown that the conditions depend on the structure of the communication graph, the parameters in the controllers, and the expected formation configurations. Finally, both simulations and real flight experiments successfully demonstrate the effectiveness of the proposed strategies.
|
|
11:20-11:40, Paper FrA12.5 | |
>Consensus Control Driven by Value Exchange |
|
Sugiyama, Daiki | Kyoto University |
Azuma, Shun-ichi | Kyoto University |
Ariizumi, Ryo | Nagoya University |
Asai, Toru | Nagoya University |
Keywords: Distributed control, Cooperative control, Networked control systems
Abstract: A multi-agent system is a system consisting of multiple agents that can make a global decision autonomously. So far, many studies have been conducted under the assumption that all agents behave cooperatively. On the other hand, in a large-scale multi-agent system such as a connected vehicle network, each agent must be owned by different owners. Thus, in such a system, the agents do not necessarily work cooperatively and each agent pursues its utility. Such a multi-agent system is modeled as a system driven by the exchange of certain values. In this paper, we address a consensus problem for a multi-agent system driven by the exchange between tokens and information. Unlike the typical consensus control, we assume that each agent has tokens and collects information from its neighbors in exchange for tokens. To this system, we derive a necessary and sufficient condition for the system to achieve consensus. This condition is characterized by the number of tokens and the network structure. Moreover, we disclose that the consensus value is given by the left eigenvector of the Perron matrix associated with the initial token distribution. Finally, we discuss the convergence property for several specific network structures.
|
|
11:40-12:00, Paper FrA12.6 | |
>Scalable Distributed Controller Synthesis for Multi-Agent Systems Using Barrier Functions and Symbolic Control |
|
Sundarsingh, David Smith | Indian Institute of Science |
Bhagiya, Jay | Indian Institute of Science |
Saharsh, Saharsh | Indian Institute of Science, Bangalore |
Chatrola, Jeel | Indian Institute of Science |
Saoud, Adnane | CentraleSupelec |
Jagtap, Pushpak | Indian Institute of Science |
Keywords: Distributed control, Formal Verification/Synthesis, Agents-based systems
Abstract: In this paper, we propose a computationally efficient symbolic controller synthesis technique for multi-agent systems. The paper focuses on synthesizing distributed controllers enforcing local temporal logic specifications along with global safety specifications for multi-agent systems. To solve the problem in a computationally efficient way, we leverage the concept of control barrier functions. In particular, we use a three-step bottom-up approach: first, the symbolic controllers for individual agents are synthesized to enforce local temporal logic specifications, then we use a notion of control barrier functions for symbolic models to compose controlled agent systems by removing unsafe transitions, and finally, we synthesize controller for the reduced composed system to ensure the satisfaction of local temporal logic specifications while ensuring global safety specification. The effectiveness of our approach is demonstrated on a multi-robot system by comparing it with the conventional monolithic symbolic control approaches.
|
|
FrA13 |
Roselle Junior 4613 |
Networked Control Systems IV |
Regular Session |
Chair: Steinberger, Martin | Graz University of Technology |
Co-Chair: Bastianello, Nicola | KTH Royal Institute of Technology |
|
10:00-10:20, Paper FrA13.1 | |
>A Unified Approach to Solve the Dynamic Consensus on the Average, Maximum, and Median Values with Linear Convergence |
|
Deplano, Diego | University of Cagliari |
Bastianello, Nicola | KTH Royal Institute of Technology |
Franceschelli, Mauro | University of Cagliari |
Johansson, Karl H. | KTH Royal Institute of Technology |
Keywords: Networked control systems, Optimization algorithms, Agents-based systems
Abstract: This manuscript proposes novel distributed algorithms for solving the dynamic consensus problem in discrete-time multi-agent systems on three different objective functions: the average, the maximum, and the median. In this problem, each agent has access to an external time-varying scalar signal and aims to estimate and track a function of all the signals by exploiting only local communications with other agents. By recasting the problem as an online distributed optimization problem, the proposed algorithms are derived based on the distributed implementation of the alternating direction method of multipliers (ADMM) and are thus amenable to a unified analysis technique. A major contribution is that of proving linear convergence of these ADMM-based algorithms for the specific dynamic consensus problems of interest, for which current results could only guarantee sub-linear convergence. In particular, the tracking error is shown to converge within a bound, whereas the steady-state error is zero. Numerical simulations corroborate the theoretical findings, empirically show the robustness of the proposed algorithms to re-initialization errors, and compare their performance with that of state-of-the-art algorithms.
|
|
10:20-10:40, Paper FrA13.2 | |
>An Emulation Approach to Sampled-Data Synchronization |
|
Barkai, Gal | Technion—Israel Institute of Technology |
Mirkin, Leonid | Technion - IIT |
Zelazo, Daniel | Technion - Israel Institute of Technology |
Keywords: Networked control systems, Sampled-data control, Cooperative control
Abstract: This work presents a novel approach for achieving state synchronization of homogeneous LTI agents to a trajectory generated by a prescribed reference generator under intermit- tent and asynchronous communication. The proposed protocol involves emulating “ideal” global analog dynamics at each agent to generate the control signal between samples. Each agent transmits the centroid state of its local emulator rather than its own state vector, which is used to update the emulators at the receiving end. The paper guarantees synchronization with a prescribed reference generator under mild assumptions on the system’s structure, persistency of connectivity, and uniform boundedness of sampling intervals. Additionally, the controller parameters are independent of the sampling interval, allowing it to be designed without any a priori knowledge of the sampling sequence. Lastly, a simplified and scalable implementation whose dimension is independent of the number of agents is also proposed.
|
|
10:40-11:00, Paper FrA13.3 | |
>Optimal Scheduling Policies for Remote Estimation of Autoregressive Markov Processes Over Time-Correlated Fading Channel |
|
Dutta, Manali | Indian Institute of Science |
Singh, Rahul | Indian Institute of Science |
Keywords: Networked control systems, Sensor networks, Filtering
Abstract: We consider the problem of optimally scheduling transmissions for remote estimation of a discrete-time autoregressive Markov process that is driven by white Gaussian noise. A sensor observes this process, and then decides to either encode the current state of this process into a data packet and attempts to transmit it to the estimator over an unreliable wireless channel modeled as a Gilbert-Elliott channel~cite{Gilbert1960capacity}~cite{Chakravorty2017structure}~cite{yao2022age}, or does not send any update. Each transmission attempt consumes lambda units of transmission power, and the remote estimator is assumed to be linear. The channel state is revealed only via the feedback (ACKslash NACK) of a transmission, and hence the channel state is not revealed if no transmission occurs. The goal of the scheduler is to minimize the expected value of an infinite-horizon cumulative discounted cost, in which the instantaneous cost is composed of the following two quantities: (i)~squared estimation error, (ii) transmission power. We posed this problem as a partially observable Markov decision process (POMDP), in which the scheduler maintains a belief about the current state of the channel, and makes decisions on the basis of the current value of the error e(t) (defined in~eqref{def:error_evolve}), and the belief state.~To aid its analysis, we introduce an easier-to-analyze ``folded POMDP.'' We then analyze this folded POMDP and show that there is an optimal scheduling policy that has threshold structure, i.e. for each value of the error e, there is a threshold bust(e) such that when the error is equal to e, this policy transmits only when the current belief state is greater than bust(e).
|
|
11:00-11:20, Paper FrA13.4 | |
>Stability of Nonlinear Systems with Two Time Scales Over a Single Communication Channel |
|
Wang, Weixuan | The University of Melbourne |
Maass, Alejandro I. | Universidad De O'Higgins |
Nesic, Dragan | University of Melbourne |
Tan, Ying | The University of Melbourne |
Postoyan, Romain | CNRS, CRAN, Université De Lorraine |
Heemels, W.P.M.H. | Eindhoven University of Technology |
Keywords: Networked control systems, Stability of hybrid systems, Nonlinear systems
Abstract: This paper studies the stabilisation problem for a class of nonlinear systems with two time scales, where only a single communication channel is available to allocate both low and high-frequency transmissions from slow and fast subsystems, respectively. A clock mechanism is proposed to govern the transmissions, and the closed-loop system is modelled by a hybrid singularly perturbed system. Singular perturbation based analysis is used to obtain individual maximum allowable transmission intervals for both slow and fast transmissions, and also to guarantee semi-global practical asymptotic stability with respect to the minimum allowable transmission interval of slow transmissions. We illustrate the results via a numerical example.
|
|
11:20-11:40, Paper FrA13.5 | |
>Stochastic Relaxation of the Maximum Allowable Delay for a Class of Networked Control Systems |
|
Schlotterbeck, Constanza | Pontificia Universidad Católica De Chile |
Gallegos, Javier A. | University of Chile |
Núñez, Felipe | Pontificia Universidad Catolica De Chile |
Keywords: Networked control systems, Stochastic systems, Stability of hybrid systems
Abstract: Stability in networked control systems has been typically addressed in the deterministic setting using the concepts of Maximum Allowable Transmit Interval (MATI) and Maximum Allowable Delay (MAD). This work looks to extend the analysis to the stochastic setting by giving conditions for uniform stability in probability when the communication delay follows a probability distribution that includes values over the deterministic MAD. Analytical conditions are given and validated through simulations using a concrete example.
|
|
11:40-12:00, Paper FrA13.6 | |
>Switched Lyapunov Function-Based Controller Synthesis for Networked Control Systems: A Computationally Inexpensive Approach |
|
Stanojevic, Katarina | Graz University of Technology |
Steinberger, Martin | Graz University of Technology |
Horn, Martin | Graz University of Technology |
Keywords: Networked control systems
Abstract: This paper presents a Lyapunov function-based control strategy for networked control systems (NCS) affected by variable time delays and data loss. A special focus is put on the reduction of the computational complexity. The crucial step to achieving computational efficiency involves defining a specific buffering mechanism that introduces an additional delay not larger than one sampling period. This allows representing the buffered NCS as a switched system, thus leading to a significant simplification of the NCS model and subsequent controller synthesis. The novel approach does not only circumvent the need for any over-approximation technique, but also leads to a strongly decreased number of optimization variables and linear matrix inequalities, allowing hereby greater flexibility with respect to additional degrees of freedom affecting the transient behavior. The performance and computational efficiency of the control strategy are demonstrated in a simulation example.
|
|
FrA14 |
Roselle Junior 4612 |
Observers for Linear Systems |
Regular Session |
Chair: Wang, Lili | University of California, Irvine |
Co-Chair: Becis-Aubry, Yasmina | Univ. of Orléans |
|
10:00-10:20, Paper FrA14.1 | |
>Split-Spectrum Based Distributed Estimator for a Continuous-Time Linear System on a Time-Varying Graph |
|
Wang, Lili | Purdue University |
Liu, Ji | Stony Brook University |
Anderson, Brian D.O. | Australian National University |
Morse, A. Stephen | Yale Univ |
Keywords: Observers for Linear systems, Distributed control, Autonomous systems
Abstract: A simply structured distributed estimator is described for estimating the state of a continuous-time, jointly observable, input free, multi-channel linear system whose sensed outputs are distributed across a fixed multi-agent network. The estimator is then extended to non-stationary networks whose neighbor graphs switch according to a switching signal with a dwell time, or switch arbitrarily under appropriate assumptions. The estimator is guaranteed to solve the problem, provided a network-widely shared gain is sufficiently large. The lower bound of the gain is derived. This is accomplished by appealing to the “split-spectrum” approach and exploiting several well-known properties of invariant subspace. The proposed estimators are inherently resilient to abrupt changes in the number of agents and communication links in the inter-agent communication graph upon which the algorithms depend, provided the network is redundantly strongly connected and redundantly jointly observable.
|
|
10:20-10:40, Paper FrA14.2 | |
>Minimum-Volume Set-Membership State Estimation of Time Varying Constrained Systems with Sporadic Measurements |
|
Becis-Aubry, Yasmina | Univ. of Orléans |
Ramdani, Nacim | University of Orléans |
Keywords: Observers for Linear systems, Estimation
Abstract: This paper presents a recursive ellipsoidal set-membership state estimation algorithm for discrete-time linear time-varying (LTV) models with additive bounded disturbances affecting state evolution and sporadic measurement equations. The state vector is subject to linear equality and/or inequality constraints, which are mathematically viewed as additional measurements. A novel approach is developed considering the unprecedented fact that, owing to equality constraints, the ellipsoid characterizing all possible values of the state vector has a zero volume and its shape matrix is non invertible. A new size criterion, the pseudo-volume, is introduced and minimized in both the prediction and correction phases.
|
|
10:40-11:00, Paper FrA14.3 | |
>Simultaneous State and Unknown Input Interval Observer for Discrete-Time Linear Switched Systems Using Peak-To-Peak Analysis |
|
Marouani, Ghassen | University of Monastir |
Dinh, Thach N. | CNAM Paris |
Wang, Zhenhua | Harbin Institute of Technology |
Ping, Xubin | Xidian University |
Raïssi, Tarek | Conservatoire National Des Arts Et Métiers |
Keywords: Observers for Linear systems, LMIs, Uncertain systems
Abstract: This paper investigates interval observer design for uncertain discrete-time linear switched systems under unknown inputs and a known switching signal. The approach introduces weighting matrices which allow one to relax design difficulties caused by classical coordinate transformation. To improve the accuracy, an L_{infty} method minimizing the peak-to-peak gain is employed to reduce the influence of unknown uncertainties. The interval observer gains are computed by solving Linear Matrix Inequality (LMI) formulated based on multiple quadratic Lyapunov functions under average dwell time switching signals.
|
|
11:00-11:20, Paper FrA14.4 | |
>Necessary and Sufficient Conditions for Simultaneous State and Input Recovery of Linear Systems with Sparse Inputs by L1-Minimization |
|
Poe, Kyle | Johns Hopkins University |
Mallada, Enrique | Johns Hopkins University |
Vidal, Rene | Johns Hopkins University |
Keywords: Observers for Linear systems, Optimization algorithms, Information theory and control
Abstract: The study of theoretical conditions for recovering sparse signals from compressive measurements has received a lot of attention in the research community. In parallel, there has been a great amount of work characterizing conditions for the recovery of both the state and the input to a linear dynamical system (LDS), including a handful of results on recovering sparse inputs. However, existing sufficient conditions for recovering sparse inputs to an LDS are conservative and hard to interpret, while necessary and sufficient conditions have not yet appeared in the literature. In this work, we provide (1) the first characterization of necessary and sufficient conditions for the existence and uniqueness of sparse inputs to an LDS, (2) the first necessary and sufficient conditions for a linear program to recover both an unknown initial state and a sparse input, and (3) simple, interpretable recovery conditions in terms of the LDS parameters. We conclude with a numerical validation of these claims and discuss implications and future directions.
|
|
11:20-11:40, Paper FrA14.5 | |
>Robust Reference Tracking of Linear Uncertain Systems Via Uncertainty Estimation and Composite Control |
|
Yang, Jun | National University of Singapore |
Jia, Xinyu | National University of Singapore |
Hou, Zhimin | National University of Singapore |
Pan, Yongping | Sun Yat-Sen University |
Yu, Haoyong | National University of Singapore |
Keywords: Observers for Linear systems, Robust control, Uncertain systems
Abstract: For linear systems with uncertainties and external disturbances, we present an uncertainty estimation and composite control (UECC) to achieve reference tracking and uncertainty estimation simultaneously. In this proposed UECC, we extract the uncertainty information from the error dynamics equation instead of the system dynamics. By reformulating the error dynamics equation as an algebraic equation using auxiliary variables, the need to measure state derivatives in the estimator and controller design is eliminated. Unlike time-delay control (TDC) and uncertainty and disturbance estimator (UDE) methods, we avoid the use of time delay and additional filtering operations to circumvent the noise amplification and oscillations in the control signal. Comparative simulations are provided to verify the effectiveness of the proposed method.
|
|
11:40-12:00, Paper FrA14.6 | |
>Synthesis of Robust State Estimation Algorithms under Unknown Sensor Inputs |
|
Khan, Shiraz | Purdue University |
Pant, Kartik Anand | Purdue University |
Hwang, Inseok | Purdue University |
Keywords: Observers for Linear systems, Stochastic systems, Time-varying systems
Abstract: The problem of estimating the state of a dynamical system using sensor measurements becomes challenging when some of the measurements are modified by unknown inputs, which can arise due to sensor faults, modeling errors, or adversarial data injection attacks. To solve this problem, several authors have developed robust state estimation algorithms by assuming that the unknown input follows a known dynamical or probabilistic model. However, to the best of our knowledge, the stability of the existing algorithms under arbitrary unknown input sequences (which may violate the assumed dynamical or probabilistic model) has not been studied in the literature. In this paper, we address this limitation by proposing and analyzing a class of robust state estimation algorithms which unifies the existing algorithms. We derive stability guarantees that are applicable to a wider range of unknown input sequences, including (but not limited to) the ones considered in the literature. Through a numerical example, it is demonstrated that the proposed robust state estimation method achieves better state estimation performance than the existing algorithms in the presence of unknown inputs.
|
|
FrA15 |
Roselle Junior 4611 |
Robust Control III |
Regular Session |
Chair: Bhowmick, Parijat | Indian Institute of Technology Guwahati |
Co-Chair: Lessard, Laurent | Northeastern University |
|
10:00-10:20, Paper FrA15.1 | |
>Robust Data-Driven Safe Control Using Density Functions |
|
Zheng, Jian | Northeastern University |
Dai, Tianyu | Northeastern University |
Miller, Jared | Northeastern University |
Sznaier, Mario | Northeastern University |
Keywords: Robust control, Uncertain systems, Optimization
Abstract: This paper presents a tractable framework for data-driven synthesis of robustly safe control laws. Given noisy experimental data and some priors about the structure of the system, the goal is to synthesize a state feedback law such that the trajectories of the closed loop system are guaranteed to avoid an unsafe set even in the presence of unknown but bounded disturbances (process noise). The main result of the paper shows that for polynomial dynamics, this problem can be reduced to a tractable convex optimization by combining elements from polynomial optimization and the theorem of alternatives. This optimization provides both a rational control law and a density function safety certificate. These results are illustrated with numerical examples.
|
|
10:20-10:40, Paper FrA15.2 | |
>Safe and Robust Stabilization of Uncertain Nonlinear Systems Via Control Lyapunov-Barrier Function and Disturbance Observer: A Preliminary Study |
|
Byeon, Sunseok | University of Seoul |
Park, Gyunghoon | University of Seoul |
Keywords: Robust control, Uncertain systems, Stability of nonlinear systems
Abstract: In this paper, we address the problem of safe and robust stabilization for a class of uncertain nonlinear systems. The key idea is to employ the disturbance observer (DOB) to a nominal safety-critical controller designed for the control Lyapunov-barrier function (CLBF). The DOB estimates and compensates the lumped disturbance that represents all the effect of model uncertainty and disturbance to the system approximately but as accurately as possible. As a result, only a small perturbation remains in the control loop, which can be dealt with as long as the nominal closed-loop system is input-tostate safe (ISSf) in a sense. To ensure the ISSf property without restriction on the CLBF, we propose a modified version of the Sontag’s universal formula as a nominal controller. This preliminary study verifies the validity of the proposed approach for 2nd-order nonlinear systems, but with mathematical analysis and simulations for the inverted pendulum on a cart.
|
|
10:40-11:00, Paper FrA15.3 | |
>Closing the Loop on Runtime Monitors with Fallback-Safe MPC |
|
Sinha, Rohan | Stanford University |
Schmerling, Edward | Stanford University |
Pavone, Marco | Stanford University |
Keywords: Robust control, Vision-based control, Fault tolerant systems
Abstract: When we rely on deep-learned models for robotic perception, we must recognize that these models may behave unreliably on inputs dissimilar from the training data, compromising the closed-loop system's safety. This raises fundamental questions on how we can assess confidence in perception systems and to what extent we can take safety-preserving actions when external environmental changes degrade our perception model's performance. Therefore, we present a framework to certify the safety of a perception-enabled system deployed in novel contexts. To do so, we leverage robust model predictive control (MPC) to control the system using the perception estimates while maintaining the feasibility of a safety-preserving fallback plan that does not rely on the perception system. In addition, we calibrate a runtime monitor using recently proposed conformal prediction techniques to certifiably detect when the perception system degrades beyond the tolerance of the MPC controller, resulting in an end-to-end safety assurance. We show that this control framework and calibration technique allows us to certify the system's safety with orders of magnitudes fewer samples than required to retrain the perception network when we deploy in a novel context on a photo-realistic aircraft taxiing simulator. Furthermore, we illustrate the safety-preserving behavior of the MPC on simulated examples of a quadrotor. We open-source our simulation platform and provide videos of our results at our project page: https://tinyurl.com/fallback-safe-mpc.
|
|
11:00-11:20, Paper FrA15.4 | |
>Real-Time Optimisation-Based Robust Control: Heat Exchanger Comparative Analysis |
|
Horváthová, Michaela | Slovak University of Technology in Bratislava |
Galčíková, Lenka | Faculty of Chemical and Food Technology, Slovak University of Te |
Klauco, Martin | Slovak University of Technology in Bratislava |
Oravec, Juraj | Slovak University of Technology in Bratislava |
Keywords: Process Control, Robust control, Optimal control
Abstract: This paper investigates a possibility to improve the control performance of a laboratory-scale heat exchanger by introducing the convex-lifting-based robust controller into the closed-loop system. Robust model predictive control (MPC) design serves as the relevant reference control strategy. The improvements are expected in both, increased performance of the control trajectories and, simultaneously, reduced computational complexity. The performance is analyzed subject to the reference tracking implemented on the laboratory plate heat exchanger. This plant has a nonlinear and asymmetric behavior, affected by various uncertain parameters. The case study investigates the robust MPC, tunable convex-lifting-based robust control, and convex-lifting-based robust control with approximated control law. This paper also extends the convex-lifting-based robust control with approximated control law to provide the robust stability guarantees. The experimental case study evaluates and analyses various apprehensible criteria, e.g., energy consumption, carbon footprint, and computational demands.
|
|
11:20-11:40, Paper FrA15.5 | |
>On State-Space Characterisation for Output Negative Imaginary Systems with Possible Poles at the Origin and Their Internal Stability Result (I) |
|
Devi, Salam Athoibi | Indian Institute of Technology Guwahati |
Bhowmick, Parijat | Indian Institute of Technology Guwahati |
Lanzon, Alexander | University of Manchester |
Keywords: Robust control, Stability of linear systems, LMIs
Abstract: This paper derives a new and unifying state-space characterisation for the entire class of real, rational, proper Output Negative Imaginary (ONI) systems, allowing poles on the imaginary axis even at the origin. The proposed result captures the existing versions of the NI state-space characterisations, particularly the ones that apply to the NI systems with poles at the origin. A necessary and sufficient LMI condition has been derived to test the strict/non-strict ONI properties of an LTI system with a given minimal state-space realisation. The LMI-based characterisation offers easy and convenient execution due to the easily accessible SDP solver packages. Finally, a necessary and sufficient internal stability theorem is also derived for a positive feedback ONI systems interconnection containing pole(s) at the origin. The proposed stability result specialises to the earlier versions when the earlier assumptions are imposed. Numerical examples are given to show the usefulness of the proposed theoretical results.
|
|
11:40-12:00, Paper FrA15.6 | |
>Guaranteed Stability Margins for Decentralized Linear Quadratic Regulators |
|
Kashyap, Mruganka | Northeastern University |
Lessard, Laurent | Northeastern University |
Keywords: Decentralized control, Robust control, Distributed control
Abstract: It is well-known that linear quadratic regulators (LQR) enjoy guaranteed stability margins, whereas linear quadratic Gaussian regulators (LQG) do not. In this letter, we consider systems and compensators defined over directed acyclic graphs. In particular, there are multiple decision-makers, each with access to a different part of the global state. In this setting, the optimal LQR compensator is dynamic, similar to classical LQG. We show that when sub-controller input costs are decoupled (but there is possible coupling between sub-controller state costs), the decentralized LQR compensator enjoys similar guaranteed stability margins to classical LQR. However, these guarantees disappear when cost coupling is introduced.
|
|
FrA16 |
Peony Junior 4512 |
Smart Grid II |
Regular Session |
Chair: Zheng, Wei Xing | Western Sydney University |
Co-Chair: Liu, Mingxi | University of Utah |
|
10:00-10:20, Paper FrA16.1 | |
>Deep Learning for Scalable Optimal Design of Incremental Volt/VAR Control Rules |
|
Gupta, Sarthak | Virginia Tech |
Mehrizi-Sani, Ali | Virginia Tech |
Chatzivasileiadis, Spyros | Technical University of Denmark |
Kekatos, Vassilis | Virginia Tech |
Keywords: Smart grid, Optimization, Neural networks
Abstract: Volt/VAR control rules enable distributed energy resources (DER) to autonomously regulate voltage in distribution grids. The Volt/VAR rules provisioned by the IEEE Standard 1547 take on a piecewise-linear shape. However, its maximum slope is upper bounded to ensure stability, and that may hamper its voltage regulation performance. This limitation can be surpassed by adding a memory term to the control rule, and thus, obtaining a so-termed incremental control rule. This letter aims to optimally customize the shape of incremental rules across buses to attain desirable voltage profiles. Albeit this task can be posed as a bilevel program, we pursue a more scalable approach by reformulating it as a deep learning task. The idea is that Volt/VAR dynamics can be captured by a recursive neural network (RNN). Interestingly, the RNN weights correspond to the parameters of the control rule; the RNN input to the grid loading conditions; and the RNN output to the equilibrium voltages. Therefore, the optimal rule parameters can be found upon training the RNN so its output (equilibrium voltages) approach unity. Training is performed by feeding the RNN with representative scenarios of the anticipated grid loading conditions. The RNN depth depends on the settling time of Volt/VAR dynamics. Because the discrete-time Volt/VAR dynamics can be viewed as iterations of a proximal gradient descent (PGD) algorithm, we also leverage Nesterov's accelerated PGD iterations to reduce the RNN depth. The RNN is never implemented in the field. Training this RNN is equivalent to solving the optimal rule design in a more computationally efficient manner. Analytical findings and numerical tests corroborate that the proposed solution can be neatly adapted to single- and multi-phase feeders. The proposed approach could be of general interest in designing piecewise-linear controllers acting on linear plants.
|
|
10:20-10:40, Paper FrA16.2 | |
>On Privacy Preservation of Electric Vehicle Charging Control Via State Obfuscation |
|
Huo, Xiang | University of Utah |
Liu, Mingxi | University of Utah |
Keywords: Smart grid, Optimization algorithms, Control Systems Privacy
Abstract: The electric vehicle (EV) industry is rapidly evolving owing to advancements in smart grid technologies and charging control strategies. While EVs are promising in decarbonizing the transportation system and providing grid services, their widespread adoption has led to notable and erratic load injections that can disrupt the normal operation of power grid. Additionally, the unprotected collection and utilization of personal information during the EV charging process cause prevalent privacy issues. To address the scalability and data confidentiality in large-scale EV charging control, we propose a novel decentralized privacy-preserving EV charging control algorithm via state obfuscation that 1) is scalable w.r.t. the number of EVs and ensures optimal EV charging solutions; 2) achieves privacy preservation in the presence of honest-but-curious adversaries and eavesdroppers; and 3) is applicable to eliminate privacy concerns for general multi-agent optimization problems in large-scale cyber-physical systems. The EV charging control is structured as a constrained optimization problem with coupled objectives and constraints, then solved in a decentralized fashion. Privacy analyses and simulations demonstrate the efficiency and efficacy of the proposed approach.
|
|
10:40-11:00, Paper FrA16.3 | |
>Fast Distributed Resource Allocation of Smart Grid: A Zeroth-Order Optimization Algorithm |
|
Luan, Meng | Southeast University |
Wen, Guanghui | Southeast University |
Zheng, Wei Xing | Western Sydney University |
Keywords: Smart grid, Optimization algorithms
Abstract: This paper investigates a multi-objective distributed resource allocation problem, where the economic cost including the transmission loss, and the environmental pollution are taken into account simultaneously. To settle this problem, a Pareto-based zeroth-order fast distributed optimization algorithm is proposed, which can always balance the overall energy demand with generation. In the algorithm design, the acceleration idea of the momentum method is tailored for the gradient estimation update, which gives a more accurate descent direction. Moreover, the unknown effect causes the gradient of the objective function to be unavailable and only the function values to be observed. Different from the gradient-based methods, a zeroth-order method is proposed to solve the distributed resource allocation problem with gradient estimation. Furthermore, the convergence of the designed algorithm is proved theoretically, and the convergence rate of linear speedup can be achieved. Finally, numerical simulations verify the validity and applicability of the proposed algorithm.
|
|
11:00-11:20, Paper FrA16.4 | |
>Multi-Objective Optimal Dispatching for Heterogeneous Multienergy Ship Microgrid (I) |
|
Ke, Shang | Yanshan University |
Li, Xiaolei | Yanshan University |
Luo, Xiaoyuan | Yanshan University |
Wang, Jiange | Yanshan University |
Xu, Qianwen | KTH Royal Institute of Technology |
Keywords: Smart grid, Optimization algorithms, Energy systems
Abstract: With the growth of energy and transportation demand, the integrated energy dispatching of ship power grid has become the focus of researchers. The optimization technique is used to reduce the total energy consumption and pollutant emissions of ships, optimizing the ship power generation planning. The purpose is to achieve environmental protection and energy saving while ensuring the continuous and reliable power supply of ships. However, heterogeneous ship microgrid poses new challenges to integrated energy dispatch. This paper proposes an integrated energy scheduling scheme that integrates photovoltaic, wind power, diesel engine, gas turbine, and battery for a heterogeneous multienergy ship microgrid. Under the system constraints, a multi-objective optimal scheduling model including operating costs and pollutant emissions is established, then the gravity search algorithm is applied to solve such an issue. The simulation results show that the scheme can effectively reduce the cost of energy consumption and pollutant emissions of ships, improving the economy, reliability and energy conservation, which verify the advantages of the proposed scheme.
|
|
11:20-11:40, Paper FrA16.5 | |
>An Exact Characterisation of Flexibility in Populations of Electric Vehicles |
|
Mukhi, Karan | University of Oxford |
Abate, Alessandro | University of Oxford |
Keywords: Smart grid, Power systems, Energy systems
Abstract: Increasing penetrations of electric vehicles (EVs) presents a large source of flexibility, which can be used to assist balancing the power grid. The flexibility of an individual EV can be quantified as a convex polytope and the flexibility of a population of EVs is the Minkowski sum of these polytopes. In general computing the exact Minkowski sum is intractable. However, exploiting symmetry in a restricted but significant case, enables an efficient computation of the aggregate flexibility. This results in a polytope with exponentially many vertices and facets with respect to the time horizon. We show how to use a lifting procedure to provide a representation of this polytope with a reduced number of facets, which makes optimising over more tractable. Finally, a disaggregation procedure that takes an aggregate signal and computes dispatch instructions for each EV in the population is presented. The complexity of the algorithms presented is independent of the size of the population and polynomial in the length of the time horizon. We evaluate this work against existing methods in the literature, and show how this method guarantees optimality with lower computational burden than existing methods.
|
|
11:40-12:00, Paper FrA16.6 | |
>Reducing Aggregate Electric Vehicle Battery Capacity through Sharing |
|
Alexeenko, Polina | Cornell University |
Charisopoulos, Vasileios | Cornell University |
Keywords: Smart grid, Power systems, Optimization
Abstract: Meeting demand for automotive battery resources is predicted to be costly from both economic and environmental perspectives. To minimize costs, battery resources should be deployed as efficiently as possible. A potential source of inefficiency in battery deployment is that the batteries of personal vehicles are typically much larger than necessary to meet most daily mobility needs. In this paper, we consider whether battery resources can be used more efficiently in a setting where drivers, in addition to having personal vehicle batteries, have access to a shared battery resource. More precisely, we consider the problem of minimizing aggregate battery capacity in settings with and without a shared resource subject to the requirement that driver commuting needs are met with high reliability. To assess capacity reduction potential, we quantify the difference in deployed battery capacity in settings with and without a shared resource in a case study using real-world longitudinal mobility data from Puget Sound, Washington. We find that access to a shared battery resource can substantially reduce deployed battery capacity. Furthermore, relative reductions in battery capacity increase with number of drivers and the level of reliability desired.
|
|
FrA17 |
Peony Junior 4511 |
Statistical Learning I |
Regular Session |
Chair: Mahajan, Aditya | McGill University |
Co-Chair: Li, Tao | East China Normal University |
|
10:00-10:20, Paper FrA17.1 | |
>Multi-Agent Reachability Calibration with Conformal Prediction |
|
Muthali, Anish | University of California, Berkeley |
Shen, Haotian | University of California, Berkeley |
Deglurkar, Sampada | University of California, Berkeley |
Lim, Michael H. | University of California, Berkeley |
Roelofs, Rebecca | University of California, Berkeley |
Faust, Aleksandra | Google |
Tomlin, Claire J. | UC Berkeley |
Keywords: Statistical learning, Autonomous vehicles, Iterative learning control
Abstract: We investigate methods to provide safety assurances for autonomous agents that incorporate predictions of other, uncontrolled agents' behavior into their own trajectory planning. Given a learning-based forecasting model that predicts agents' trajectories, we introduce a method for providing probabilistic assurances on the model's prediction error with calibrated confidence intervals. Through quantile regression, conformal prediction, and reachability analysis, our method generates probabilistically safe and dynamically feasible prediction sets. We showcase their utility in certifying the safety of planning algorithms, both in simulations using actual autonomous driving data and in an experiment with Boeing vehicles.
|
|
10:20-10:40, Paper FrA17.2 | |
>Error Analysis of Regularized Trigonometric Linear Regression with Unbounded Sampling: A Statistical Learning Viewpoint |
|
Scampicchio, Anna | ETH Zurich |
Arcari, Elena | ETH Zurich |
Zeilinger, Melanie N. | ETH Zurich |
Keywords: Statistical learning, Estimation
Abstract: The effectiveness of non-parametric, kernel-based methods for function estimation comes at the price of high computational complexity, which hinders their applicability in adaptive, model-based control. Motivated by approximation techniques based on sparse spectrum Gaussian processes, we focus on models given by regularized trigonometric linear regression. This paper provides an analysis of the performance of such an estimation set-up within the statistical learning framework. In particular, we derive a novel bound for the sample error in finite-dimensional spaces, accounting for noise with potentially unbounded support. Next, we study the approximation error and discuss the bias-variance trade-off as a function of the regularization parameter by combining the two bounds.
|
|
10:40-11:00, Paper FrA17.3 | |
>Online Learning in Reproducing Kernel Hilbert Space with Non-IID Data |
|
Zhang, Xiwei | East China Normal University |
Li, Tao | East China Normal University / New York University Shanghai |
Keywords: Statistical learning, Distributed parameter systems, Adaptive systems
Abstract: We analyze the convergence of online regularized learning algorithm based on dependent and non-stationary online data streams for the nonparametric regression problem in reproducing kernel Hilbert space (RKHS). We show that the algorithm achieves mean-square convergence if the algorithm gain and regularization parameter are chosen appropriately, the online data streams are weakly dependent and satisfy the eigenvalue-wise persistence of excitation condition. Especially, for the case with independent but non-identically distributed online data streams, we give more intuitive convergence conditions on the drifts of the probability measures induced by the data.
|
|
11:00-11:20, Paper FrA17.4 | |
>Estimation of Models with Limited Data by Leveraging Shared Structure |
|
Rui, Maryann | Massachusetts Institute of Technology |
Horel, Thibaut | MIT |
Dahleh, Munther A. | Massachusetts Inst. of Tech |
Keywords: Statistical learning, Identification, Learning
Abstract: Modern data sets, such as those in healthcare and e-commerce, are often derived from many individuals or systems but have insufficient data from each source alone to separately estimate individual, often high-dimensional, model parameters. If there is shared structure among systems however, it may be possible to leverage data from other systems to help estimate individual parameters, which could otherwise be non-identifiable. In this paper, we assume systems share a latent low-dimensional parameter space and propose a method for recovering d-dimensional parameters for N different linear systems, when there are only T
|
|
11:20-11:40, Paper FrA17.5 | |
>On the Hardness of Learning to Stabilize Linear Systems |
|
Zeng, Xiong | University of Michigan, Ann Arbor |
Liu, Zexiang | University of Michigan |
Du, Zhe | University of Michigan |
Ozay, Necmiye | Univ. of Michigan |
Sznaier, Mario | Northeastern University |
Keywords: Statistical learning, Linear systems, Uncertain systems
Abstract: Inspired by the work of Tsiamis et al. [1], in this paper we study the statistical hardness of learning to stabilize linear time-invariant systems. Hardness is measured by the number of samples required to achieve a learning task with a given probability. The work in [1] shows that there exist system classes that are hard to learn to stabilize with the core reason being the hardness of identification. Here we present a class of systems that can be easy to identify, thanks to a non-degenerate noise process that excites all modes, but the sample complexity of stabilization still increases exponentially with the system dimension. We tie this result to the hardness of co-stabilizability for this class of systems using ideas from robust control.
|
|
11:40-12:00, Paper FrA17.6 | |
>Relative Almost Sure Regret Bounds for Certainty Equivalence Control of Markov Jump Systems |
|
Sayedana, Borna | McGill University |
Afshari, Mohammad | McGill University |
Caines, Peter E. | McGill University |
Mahajan, Aditya | McGill University |
Keywords: Statistical learning, Machine learning, Adaptive control
Abstract: In this paper, we consider learning and control problem in an unknown Markov jump linear system (MJLS) with perfect state observations. We first establish a generic upper bound on regret for any learning based algorithm. We then propose a certainty equivalence-based learning algorithm and show that this algorithm achieves a regret of O(sqrt(T)log(T)) relative to a certain subset of the sample space. As part of our analysis, we revisit the switched least squares system identification algorithm of [1], [2] for autonomous MJLS and generalize it to controlled MJLS, establishing strong consistency and almost sure rates of convergence of this method.
|
|
FrA18 |
Peony Junior 4412 |
Stability of Nonlinear Systems III |
Regular Session |
Chair: Efimov, Denis | Inria |
Co-Chair: Mauroy, Alexandre | University of Namur |
|
10:00-10:20, Paper FrA18.1 | |
>Homogeneity with Respect to a Part of Variables and Accelerated Stabilization |
|
Efimov, Denis | Inria |
Kolmanovsky, Ilya V. | The University of Michigan |
Keywords: Stability of nonlinear systems, Nonholonomic systems
Abstract: The problem of transforming a locally asymptotically stabilizing time-varying control law to a globally stabilizing one with accelerated finite/fixed-time convergence is studied. The solution is based on an extension of the theory of homogeneous systems to the setting where the symmetry and stability properties only hold with respect to a part of the state variables. The proposed control design advances the kind of approaches first studied in [M'Closkey&Murray,1997], and relies on the implicit Lyapunov function framework. Examples of finite-time and nearly fixed-time stabilization of a nonholonomic integrator are reported.
|
|
10:20-10:40, Paper FrA18.2 | |
>On the Computation of Principal Eigenfunctions of the Koopman Operator |
|
Deka, Shankar | KTH Royal Institute of Technology, Sweden |
Krishnamoorthy Shankara Narayanan, Sriram Sundar | Clemson University |
Vaidya, Umesh | Clemson University |
Keywords: Stability of nonlinear systems, Lyapunov methods, Neural networks
Abstract: The paper is about the computation of the principal spectrum of the Koopman operator (i.e., eigenvalues and eigenfunctions). The principal eigenfunctions of the Koopman operator are the ones with the corresponding eigenvalues equal to the eigenvalues of the linearization of the nonlinear system at an equilibrium point. The main contribution of this paper is to provide a novel approach for computing the principal eigenfunctions using a path-integral formula. Furthermore, we provide conditions based on the stability property of the dynamical system and the eigenvalues of the linearization towards computing the principal eigenfunction using the path-integral formula. Further, we provide a Deep Neural Network framework that utilizes our proposed path-integral approach for eigenfunction computation in high-dimension systems. Finally, we present simulation results for the computation of principal eigenfunction and demonstrate their application for determining the stable and unstable manifolds and constructing the Lyapunov function.
|
|
10:40-11:00, Paper FrA18.3 | |
>Design of Controls for Boundedness of Trajectories of Multistable State Periodic Systems |
|
Mendoza-Avila, Jesus | INRIA Lille-Nord Europe |
Efimov, Denis | Inria |
Mercado Uribe, José Angel | Brandenburgische Technische Universität Cottbus-Senftenberg |
Schiffer, Johannes | Brandenburg University of Technology |
Keywords: Stability of nonlinear systems, Nonlinear systems, Lyapunov methods
Abstract: In this paper, the concept of control Leonov functions is introduced, and it is shown that their information is enough to design continuous and periodic controllers that provide boundedness of the state for a class of multistable state-periodic systems. These feedback control laws are based on a mild adaptation of Sontag's universal formula and a kind of small control property. The proposed method is illustrated via application in a microgrid.
|
|
11:00-11:20, Paper FrA18.4 | |
>On Systematic Criteria for the Global Stability of Nonlinear Systems Via the Koopman Operator Framework |
|
Zagabe, Christian Mugisho | University of Namur |
Mauroy, Alexandre | University of Namur |
Keywords: Stability of nonlinear systems, Lyapunov methods, Nonlinear systems
Abstract: We present novel sufficient conditions for the global stability of an equilibrium in the case of nonlinear dynamics with analytic vector fields. These conditions provide stability criteria that are directly expressed in terms of the Taylor expansion coefficients of the vector field (e.g. in terms of first order coefficients, maximal coefficient, sum of coefficients). Our main assumptions is that the vector field components be holomorphic, and the linearized system be locally exponentially stable and diagonalizable. These results are based on the properties of the Koopman operator defined on the Hardy space on the polydisc.
|
|
11:20-11:40, Paper FrA18.5 | |
>Global Asymptotic Stabilization of Time-Invariant Bilinear Non-Homogeneous Complex Systems |
|
Zaitsev, Vasilii | Udmurt State University |
Keywords: Stability of nonlinear systems, Lyapunov methods
Abstract: The problem of global asymptotic stabilization by state feedback is considered for time-invariant bilinear non-homogeneous control systems in the complex space. For such systems, the possibility of applying the second Lyapunov method is proved, which is not valid for general nonlinear complex systems. The approach uses the Barbashin--Krasovsky--La Salle theorem on global asymptotic stability. Sufficient conditions for global asymptotic stabilization of a bilinear non-homogeneous complex system by real state feedback are obtained. Finally, an example of using the obtained results is presented.
|
|
11:40-12:00, Paper FrA18.6 | |
>A Recurrence-Based Direct Method for Stability Analysis and GPU-Based Verification of Non-Monotonic Lyapunov Functions |
|
Siegelmann, Roy | Johns Hopkins University |
Shen, Yue | Johns Hopkins University |
Paganini, Fernando | Universidad ORT Uruguay |
Mallada, Enrique | Johns Hopkins University |
Keywords: Stability of nonlinear systems, Numerical algorithms, Lyapunov methods
Abstract: Lyapunov's direct method is a powerful tool that provides a rigorous framework for stability analysis and control design for dynamical systems. A critical step that enables the application of the method is the existence of a Lyapunov function V---a function whose value monotonically decreases along the trajectories of the dynamical system. Unfortunately, finding a Lyapunov function is often tricky and requires ingenuity, domain knowledge, or significant computational power. At the core of this challenge is the fact that the method requires every sub-level set of V (V_{leq c}) to be forward invariant, thus implicitly coupling the geometry of V_{leq c} and the trajectories of the system. In this paper, we seek to disentangle this dependence by developing a direct method that substitutes the concept of invariance with the more flexible notion of recurrence. A set is (tau-)recurrent if every trajectory that starts in the set returns to it (within tau seconds). We show that, under mild conditions, the recurrence of sub-level sets V_{leq c} is sufficient to guarantee stability and introduce the appropriate stronger notions to obtain asymptotic stability and exponential stability. We further provide a GPU-based algorithm to verify whether V satisfies such recurrence conditions up to an arbitrarily small neighborhood of the equilibrium.
|
|
FrA19 |
Peony Junior 4411 |
Predictive Control for Linear Systems II |
Regular Session |
Chair: Allgöwer, Frank | University of Stuttgart |
Co-Chair: Schulze Darup, Moritz | TU Dortmund University |
|
10:00-10:20, Paper FrA19.1 | |
>Implicit Predictors in Regularized Data-Driven Predictive Control |
|
Klädtke, Manuel | TU Dortmund University |
Schulze Darup, Moritz | TU Dortmund University |
Keywords: Predictive control for linear systems, Optimal control, Subspace methods
Abstract: We introduce the notion of implicit predictors, which characterize the input-(state)-output prediction behavior underlying a predictive control scheme, even if it is not explicitly enforced as an equality constraint (as in traditional model or subspace predictive control). To demonstrate this concept, we derive and analyze implicit predictors for some basic data-driven predictive control (DPC) schemes, which offers a new perspective on this popular approach that may form the basis for modified DPC schemes and further theoretical insights.
|
|
10:20-10:40, Paper FrA19.2 | |
>Towards Grassmanian Dimensionality Reduction in MPC |
|
Schurig, Roland | TU Darmstadt, Control and Cyber-Physical Systems Laboratory |
Himmel, Andreas | TU Darmstadt |
Findeisen, Rolf | TU Darmstadt |
Keywords: Predictive control for linear systems, Optimization, Model/Controller reduction
Abstract: Model predictive control presents remarkable po- tential for the optimal control of dynamic systems. However, the necessity for an online solution to an optimal control problem often renders it impractical for control systems with limited computational capabilities. To address this issue, specialized dimensionality reduction techniques designed for optimal con- trol problems have been proposed. In this paper, we introduce a methodology for designing a low-dimensional subspace that provides an ideal representation for a predefined finite set of high-dimensional optimizers. By characterizing the subspace as an element of a specific Riemannian manifold, we leverage the unique geometric structure of the subspace. Subsequently, the optimal subspace is identified through optimization on the Riemannian manifold. The dimensionality reduction for the model predictive control scheme is achieved by confining the search space to the optimized low-dimensional subspace, enhancing both efficiency and applicability.
|
|
10:40-11:00, Paper FrA19.3 | |
>Efficient Computation of Lipschitz Constants for MPC with Symmetries |
|
Teichrib, Dieter | TU Dortmund University |
Schulze Darup, Moritz | TU Dortmund University |
Keywords: Predictive control for linear systems, Optimization, Optimal control
Abstract: Lipschitz constants for linear MPC are useful for certifying inherent robustness against unmodeled disturbances or robustness for neural network-based approximations of the control law. In both cases, knowing the minimum Lipschitz constant leads to less conservative certifications. Computing this minimum Lipschitz constant is trivial given the explicit MPC. However, the computation of the explicit MPC may be intractable for complex systems. The paper discusses a method for efficiently computing the minimum Lipschitz constant without using the explicit control law. The proposed method simplifies a recently presented mixed-integer linear program (MILP) that computes the minimum Lipschitz constant. The simplification is obtained by exploiting saturation and symmetries of the control law and irrelevant constraints of the optimal control problem.
|
|
11:00-11:20, Paper FrA19.4 | |
>On Stochastic MPC Formulations with Closed-Loop Guarantees: Analysis and a Unifying Framework |
|
Köhler, Johannes | ETH Zurich |
Geuss, Ferdinand | Eidgenössische Technische Hochschule Zürich |
Zeilinger, Melanie N. | ETH Zurich |
Keywords: Predictive control for linear systems, Stochastic optimal control, Constrained control
Abstract: We investigate model predictive control (MPC) formulations for linear systems subject to i.i.d. stochastic disturbances with bounded support and chance constraints. Existing stochastic MPC formulations with closed-loop guarantees can be broadly classified in two separate frameworks: i) using robust techniques; ii) feasibility preserving algorithms. We investigate two particular MPC formulations representative for these two frameworks called robust-stochastic MPC and indirect feedback stochastic MPC. We provide a qualitative analysis, highlighting intrinsic limitations of both approaches in different edge cases. Then, we derive a unifying stochastic MPC framework that naturally includes these two formulations as limit cases. This qualitative analysis is complemented with numerical results, showcasing the advantages and limitations of each method.
|
|
11:20-11:40, Paper FrA19.5 | |
>Stochastic Model Predictive Control Using Initial State and Variance Interpolation |
|
Schlüter, Henning | University Stuttgart |
Allgöwer, Frank | University of Stuttgart |
Keywords: Predictive control for linear systems, Stochastic optimal control, Stochastic systems
Abstract: We present a Stochastic Model Predictive Control (SMPC) framework for linear systems subject to Gaussian disturbances. In order to avoid feasibility issues, we employ a recent initialization strategy, optimizing over an interpolation of the initial state between the current measurement and previous prediction. By also considering the variance in the interpolation, we can employ variable-size tubes, to ensure constraint satisfaction in closed-loop. We show that this novel method improves control performance and enables following the constraint closer, then previous methods. Using a DC-DC converter as numerical example we illustrated the improvement over previous methods.
|
|
11:40-12:00, Paper FrA19.6 | |
>Model Predictive Control in Partially Observable Multi-Modal Discrete Environments |
|
Rosolia, Ugo | Caltech |
Guastella, Dario Calogero | University of Catania |
Muscato, Giovanni | Universita Degli Studi Di Catania |
Borrelli, Francesco | Unversity of California at Berkeley |
Keywords: Predictive control for linear systems, Uncertain systems, Markov processes
Abstract: Autonomous systems operate in environments that can be observed only through noisy measurements. Thus, controllers should compute actions based on their beliefs about the surroundings. In these settings, we design a Model Predictive Controller (MPC) based on a continuous-state Linear Time-Invariant (LTI) system model operating in a discrete-state environment described by a Hidden Markov Model (HMM). Environment constraints are modeled as chance constraints and environment observations can be asynchronous with system state measurements and controller updates. We show how to approximate the solution of the MPC problem defined over the space of feedback policies by optimizing over a trajectory tree, where each branch is associated with an environment measurement. The proposed approach guarantees chance constraint satisfaction and recursive feasibility. Finally, we test the proposed strategy on navigation examples in partially observable environments, where the proposed MPC guarantees chance constraint satisfaction.
|
|
FrA20 |
Orchid Junior 4312 |
Modelling and Control I |
Regular Session |
Chair: Moreschini, Alessio | Imperial College London |
Co-Chair: Tebaldi, Davide | University of Modena and Reggio Emilia |
|
10:00-10:20, Paper FrA20.1 | |
>Model Reduction in the Loewner Framework for Second-Order Network Systems on Graphs |
|
Moreschini, Alessio | Imperial College London |
Simard, Joel David | Imperial College London |
Astolfi, Alessandro | Imperial College & Univ. of Rome |
Keywords: Reduced order modeling, Networked control systems, Large-scale systems
Abstract: This paper studies the model reduction problem in the Loewner framework for second-order network systems evolving on graphs. The selection of particular sets of tangential interpolation data allows constructing reduced order models which interpolate the underlying network system while preserving the second-order structure of the system. The conditions that the tangential interpolation data must satisfy are established on the basis of the block structure of the Loewner matrices. We use this result to link the Loewner matrices to the cluster matrix gained by partitioning the graph associated with the underlying model. Finally, we provide an illustrative example to validate the obtained results.
|
|
10:20-10:40, Paper FrA20.2 | |
>Towards Bias Correction of FedAvg Over Nonuniform and Time-Varying Communications |
|
Xiang, Ming | Northeastern University |
Ioannidis, Stratis | Northeastern University |
Yeh, Edmund | Northeastern University |
Joe-Wong, Carlee | CMU |
Su, Lili | Northeastern University |
Keywords: Machine learning, Optimization algorithms, Decentralized control
Abstract: Federated learning (FL) is decentralized machine learning framework wherein a parameter server (PS) and a collection of clients collaboratively trains a model. Communication bandwidth is a scarce resource. In each round, the PS aggregates the updates from a subset of clients only. In this paper, we consider non-uniform and time-varying communication between the PS and the clients. Specifically, in each round t, the link between the PS and client i is active with probability pit, which is unknown to both the PS and the clients. This arises when the channel conditions are heterogeneous across clients and are changing over time. We show that when the pit's are not uniform (i.e., not identical over i), Federated Average (FedAvg) -- the most widely adopted FL algorithm -- fails to minimize the global objective. Observing this, we propose Federated Postponed Broadcast (FedPBC) which is a simple variant of FedAvg; it differs from FedAvg in that the PS postpones broadcasting the global model till the end of each round. FedPBC converges to a stationary point. Moreover, the staleness is mild and there is no significant slowdown. Both theoretical analysis and numerical results are provided. On the technical front, postponing the global model broadcasts enables implicit gossiping among the clients with active links at round t. Consequently, we are able to control the perturbation of the global model dynamics caused by non-uniform and time-varying pit via the techniques of controlling gossip-type information mixing errors.
|
|
10:40-11:00, Paper FrA20.3 | |
>Lyapunov Based Time Varying Subregional Control of System with Distributed Parameters |
|
Heining, André | University of Stuttgart |
Sawodny, Oliver | University of Stuttgart |
Keywords: Flexible structures, Mechatronics, Distributed parameter systems
Abstract: An increased size of optical reflective elements, e.g., in the trend of large telescopes, requires thin structures to maintain a little mass for regaining performance in a change of orientation for example. However, exciting such a compliant structure leads to vibrations. Often, the whole surface is actively damped, although only a subregion might be exposed. Thus, a state feedback for the control of a subregion is derived by utilizing a Lyapunov function, deduced from mechanical energy. The method is then extended towards a time varying subregion. A simulation of a vibrating thin circular plate shows that the proposed method outperforms a linear quadratic regulator and that the time varying feedback law renders the closed loop stable.
|
|
11:00-11:20, Paper FrA20.4 | |
>Hybrid Dynamical Control for Discharging Rate Consensus in AC-Bus Microgrids |
|
Merchán Riveros, María Camila | Universidad De Sevilla |
Albea, Carolina | University of Seville, Spain |
Keywords: Stability of hybrid systems, Distributed control, Energy systems
Abstract: In this work, a robust distributed hybrid algorithm is proposed for the primary and secondary control loops of an island AC-bus microgrid to provide large-signal stability of the complete system. A secondary control loop is designed from droop control and multi-agent systems theory to ensure that the State Of Charge (SOC) of the batteries in discharging mode converges to a consensus. Furthermore, this distributed strategy ensures robustness with respect to any plug-and-play event or communication failure. The DC-AC power converter of each battery in discharging mode is controlled in the primary loop by using hybrid dynamical system theory, which considers non-trivial issues in the model (switching and affine terms) and in the signals (constraints in the dwell time). A suited selection of gains allows using singular perturbation analysis to provide large-signal stability properties for the complete nonlinear model.
|
|
11:20-11:40, Paper FrA20.5 | |
>A Dual Control Approach to Solve Exploration vs. Exploitation Trade-Offs in the Design of Personalized Physical Exercise Sessions |
|
Jackson, Roxanne, R. | Technical University of Berlin |
Varagnolo, Damiano | NTNU - Norwegian University of Science and Technology |
Knorn, Steffi | TU Berlin |
Keywords: Optimal control, Identification, Healthcare and medical systems
Abstract: Using biofeedback in medical therapies has proven to be effective for adapting patient behaviors while keeping the patients engaged and motivated in an exercise session. This paper considers general problems in personalized exercise sessions where the input is opportune biofeedback and the session goal is to maximize a particular exercise effect. Due to the individual differences between patients and their physiological signals, however, personalized patient models also need to be identified. With the two objectives: 1) maximize a training effect with minimal control effort, and 2) identify the individualized patient model, we have a typical exploration vs. exploration trade-off. Control problems of this form are called textit{dual control} problems. In this paper, we formulate a dual control problem for a personalized exercise session and test the approach against classical optimal control and optimal experimental design approaches in an illustrative example of performing Kegel exercises where the control and identification goals conflict with each other.
|
|
11:40-12:00, Paper FrA20.6 | |
>Control of Nonlinear Systems under Multiple Time-Varying Output Constraints: A Single Funnel Approach |
|
Mehdifar, Farhad | KTH Royal Institute of Technology |
Lindemann, Lars | University of Southern California |
Bechlioulis, Charalampos P. | University of Patras |
Dimarogonas, Dimos V. | KTH Royal Institute of Technology |
Keywords: Nonlinear systems, Constrained control, Uncertain systems
Abstract: This paper proposes a novel control framework for handling (potentially coupled) multiple time-varying output constraints for uncertain nonlinear systems. First, it is shown that the satisfaction of multiple output constraints boils down to ensuring the positiveness of a scalar variable (the signed distance from the time-varying output-constrained set's boundary). Next, a single funnel constraint is designed properly, whose satisfaction ensures convergence to and invariance of the time-varying output-constrained set. Then a robust and low-complexity funnel-based feedback controller is designed employing the prescribed performance control method. Finally, a simulation example clarifies and verifies the proposed approach.
|
|
FrA21 |
Orchid Junior 4311 |
Extremum-Seeking Control |
Regular Session |
Chair: Guay, Martin | Queens University |
Co-Chair: Wang, Shimin | Queen's University |
|
10:00-10:20, Paper FrA21.1 | |
>Exponential Extremum Seeking with Unbiased Convergence |
|
Yilmaz, Cemal Tugrul | UC San Diego |
Diagne, Mamadou | University of California San Diego |
Krstic, Miroslav | University of California, San Diego |
Keywords: Extremum seeking, Optimization
Abstract: We present a multivariable extremum seeking (ES) algorithm for static and dynamic maps that achieves unbiased convergence to the optimum exponentially, referred to as exponential ES. The conventional ES approach, which uses constant amplitude sinusoids, results in steady-state oscillations around the optimum and is unable to guarantee unbiased convergence. In contrast, our ES approach employs exponential decay and growth functions to gradually decrease the amplitude of the perturbation signal and increase the amplitude of the demodulation signal, respectively. This eliminates the steady-state oscillation. To achieve unbiased convergence, we choose an adaptation gain that is sufficiently larger than the decay rate of the perturbation so that the learning process outpaces the perturbation’s waning. The stability analysis is based on state transformation, averaging, and singular perturbation methods applied to the transformed system resulting in local stability of the transformed system as well as local exponential stability of the original system. For numerical simulation, we consider the problem of source seeking by a 2D velocity actuated point.
|
|
10:20-10:40, Paper FrA21.2 | |
>An Adaptive Extremum Seeking Scheme for Non-Convex Optimisation |
|
Mimmo, Nicola | University of Bologna |
Marconi, Lorenzo | Univ. Di Bologna |
Keywords: Extremum seeking, Adaptive systems, Optimization
Abstract: The paper presents an extremum-seeking scheme in which the dither is adaptively tuned to deal with non-convex cost functions. The adaptation law decreases the dither when local cost function trends are easily visible from output data. Contrarily, when the cost function does not have a dominant trend, the dither is increased to enrich the output data. This adaptive scheme can give advantages in practical applications when a conservatively large dither implies unnecessary high energy to optimise a cost function corrupted by non-uniform state-dependent disturbances. Numerical comparisons confirm the superior performance of the proposed solution.
|
|
10:40-11:00, Paper FrA21.3 | |
>Data-Efficient Static Cost Optimization Via Extremum-Seeking Control with Kernel-Based Function Approximation |
|
Weekers, Wouter | Eindhoven University of Technology |
Saccon, Alessandro | Eindhoven University of Technology |
Van De Wouw, Nathan | Eindhoven University of Technology |
Keywords: Extremum seeking, Machine learning, Data driven control
Abstract: We present a novel type of sampled-data extremum-seeking control (ESC) aimed at speeding up convergence to the optimum and reducing the number of costly performance measurements in practical applications. The approach uses collected output measurements to construct online an approximation of the system’s steady-state performance function using kernel-based function approximation. In regions where this approximation is detected to be sufficiently accurate, the proposed approach utilizes it to determine the search direction and compute a suitable optimizer gain for the update step. In regions where the approximation is not yet accurate, additional data is collected and employed in a ‘standard’ ESC update step, while also using it to refine the approximation of the performance function. By using the approximation of the performance function to determine the search direction and optimizer gain when possible, the number of required performance measurements and parameter update steps can be significantly reduced, e.g., with respectively 75% and 45% in our simulation study involving a static cost function.
|
|
11:00-11:20, Paper FrA21.4 | |
>A Robust Time-Delay Approach to Continuous-Time Extremum Seeking for Multi-Variable Static Map |
|
Yang, Xuefei | Harbin Institute of Technology |
Fridman, Emilia | Tel-Aviv Univ |
Keywords: Extremum seeking, Delay systems, Robust control
Abstract: In this article, we introduce a time-delay approach to gradient-based extremum seeking (ES) in the continuous domain for n-dimensional (nD) static quadratic maps. As in the recently introduced (for 2D maps in the continuous domain), we transform the system to the time-delay one (neutral type system). This system is O(varepsilon)-perturbation of the averaged linear ODE system. We further explicitly present the neutral system as the linear ODE, where O(varepsilon)-terms are considered as disturbances with distributed delays of the length of the small parameter varepsilon. Quantitative (for uncertain map) and qualitative (for unknown map) practical stability analyses are provided by employing a variation of constants formula that greatly simplifies the results compared to the previously used Lyapunov-Krasovskii (L-K) method. The new approach also simplifies the conditions and improves the results. Examples from the literature illustrate the efficiency of the new approach, allowing essentially large uncertainty of the Hessian matrix with bounds on varepsilon that are not too small.
|
|
11:20-11:40, Paper FrA21.5 | |
>Semi-Global Practical Extremum Seeking with Practical Safety |
|
Williams, Alan | UCSD |
Krstic, Miroslav | University of California, San Diego |
Scheinker, Alexander | Los Alamos National Lab |
Keywords: Extremum seeking, Optimization algorithms
Abstract: We introduce a type of safe extremum seeking (ES) controller, which minimizes an unknown objective function while also maintaining practical positivity of an unknown barrier function. We show semi-global practical asymptotic stability of our algorithm and present an analogous notion of practical safety. The dynamics of the controller are inspired by the quadratic program (QP) based safety filter designs which, in the literature, are more commonly used in cases where the barrier function is known. Conditions on the barrier and objective function are explored showing that non convex problems can be solved. A Lyapunov argument is proposed to achieve the main results of the paper. Finally, an example is given of the algorithm which solves the constrained optimization problem.
|
|
11:40-12:00, Paper FrA21.6 | |
>Output Regulation of Second-Order Nonlinear Systems Subject to Unknown Control Direction Using Extremum Seeking Control |
|
Harry, Telema | Queen's University |
Guay, Martin | Queens University |
Wang, Shimin | Queen's University |
Keywords: Extremum seeking, Output regulation, Adaptive systems
Abstract: The Nussbaum gain approach has been the standard technique in solving unknown control direction problems. In this paper, we propose control laws composed of extremum seeking control, an internal model, and a compensator signal to solve the robust practical output regulation problem of a second-order system subject to an unknown control direction. Using the Lie bracket approximation technique, we show that the closed-loop system is bounded and the origin is (epsilon)Semi-global Practical Uniform Asymptotic Stable. Finally, we illustrate the effectiveness of the proposed approach with a numerical example of a Van der Pol system.
|
|
FrA22 |
Orchid Junior 4212 |
Optimal Transport: Theory and Applications in Systems and Control |
Invited Session |
Chair: Chen, Yongxin | Georgia Institute of Technology |
Co-Chair: Ringh, Axel | Chalmers University of Technology and the University of Gothenburg |
Organizer: Chen, Yongxin | Georgia Institute of Technology |
Organizer: Haasler, Isabel | École Polytechnique Fédérale De Lausanne |
Organizer: Karlsson, Johan | KTH Royal Institute of Technology |
Organizer: Ringh, Axel | Chalmers University of Technology and the University of Gothenburg |
|
10:00-10:20, Paper FrA22.1 | |
>Mean Field Type Control with Species Dependent Dynamics Via Structured Tensor Optimization |
|
Ringh, Axel | Chalmers University of Technology and the University of Gothenbu |
Haasler, Isabel | École Polytechnique Fédérale De Lausanne |
Chen, Yongxin | Georgia Institute of Technology |
Karlsson, Johan | KTH Royal Institute of Technology |
Keywords: Cooperative control, Stochastic systems, Optimization
Abstract: In this work we consider mean field type control problems with multiple species that have different dynamics. We formulate the discretized problem using a new type of entropy-regularized multimarginal optimal transport problems where the cost is a decomposable structured tensor. A novel algorithm for solving such problems is derived, using this structure and leveraging recent results in entropy-regularized optimal transport. The algorithm is then demonstrated on a numerical example in robot coordination problem for search and rescue, where three different types of robots are used to cover a given area at minimal cost.
|
|
10:20-10:40, Paper FrA22.2 | |
>A Matching Principle for Power Transfer in Stochastic Thermodynamics |
|
Movilla Miangolarra, Olga | University of Calfornia, Irvine |
Taghvaei, Amirhossein | University of Washington Seattle |
Georgiou, Tryphon T. | University of California, Irvine |
Keywords: Stochastic optimal control, Stochastic systems
Abstract: Gradients in temperature and particle concentration fuel many processes in the physical and biological world. In the present work we study a thermodynamic engine powered by anisotropic thermal excitation (that may be due to e.g., a temperature gradient), and draw parallels with the well-known principle of impedance matching in circuit theory, where for maximal power transfer, the load voltage needs to be half of that of the supplying power source. We maximize power output of the thermodynamic engine at steady-state and show that the optimal reactive force is precise half of that supplied by the anisotropy.
|
|
10:40-11:00, Paper FrA22.3 | |
>Optimal Transport Particle Filters (I) |
|
Al-Jarrah, Mohammad | University of Washington Seattle |
Hosseini, Bamdad | University of Washington Seattle |
Taghvaei, Amirhossein | University of Washington Seattle |
Keywords: Filtering, Optimization, Statistical learning
Abstract: This paper is concerned with the theoretical and computational development of a new class of nonlinear filtering algorithms called optimal transport particle filters (OTPF). The algorithm is based on a recently introduced variational formulation of the Bayes' rule, which aims to find the Brenier optimal transport map between the prior and the posterior distributions as the solution to a stochastic optimization problem. On the theoretical side, the existing methods for the error analysis of particle filters and stability results for optimal transport map estimation are combined to obtain uniform error bounds for the filter's performance in terms of the optimization gap in solving the variational problem. The error analysis reveals a bias-variance trade-off that can ultimately be used to understand if/when the curse of dimensionality can be avoided in these filters. On the computational side, the proposed algorithm is evaluated on a nonlinear filtering example in comparison with the ensemble Kalman filter (EnKF) and the sequential importance resampling (SIR) particle filter.
|
|
11:00-11:20, Paper FrA22.4 | |
>Optimal Transport for Correctional Learning (I) |
|
Winqvist, Rebecka | KTH Royal Institute of Technology |
Lourenço, Inês | KTH Royal Institute of Technology |
Quinzan, Francesco | KTH Royal Institute of Technology |
Rojas, Cristian R. | KTH Royal Institute of Technology |
Wahlberg, Bo | KTH Royal Institute of Technology |
Keywords: Identification, Estimation, Learning
Abstract: The contribution of this paper is a generalized formulation of correctional learning using optimal transport, which is about how to optimally transport one mass distribution to another. Correctional learning is a framework developed to enhance the accuracy of parameter estimation processes by means of a teacher-student approach. In this framework, an expert agent, referred to as the teacher, modifies the data used by a learning agent, known as the student, to improve its estimation process. The objective of the teacher is to alter the data such that the student's estimation error is minimized, subject to a fixed intervention budget. Compared to existing formulations of correctional learning, our novel optimal transport approach provides several benefits. It allows for the estimation of more complex characteristics as well as the consideration of multiple intervention policies for the teacher. We evaluate our approach on two theoretical examples, and on a human-robot interaction application in which the teacher's role is to improve the robots performance in an inverse reinforcement learning setting.
|
|
11:20-11:40, Paper FrA22.5 | |
>High-Dimensional Optimal Density Control with Wasserstein Metric Matching (I) |
|
Ma, Shaojun | Goldman Sachs |
Hou, Mengxue | University of Notre Dame |
Ye, Xiaojing | Georgia State University |
Zhou, Hao-Min | Georgia Inst. of Tech |
Keywords: Optimal control, Computational methods, Neural networks
Abstract: We present a novel computational framework for density control in high-dimensional state spaces. The considered dynamical system consists of a large number of indistinguishable agents whose behaviors can be collectively modeled as a time-evolving probability distribution. The goal is to steer the agents without collision from an initial distribution to reach (or approximate) a given target distribution within a fixed time horizon at minimum cost. To tackle this problem, we propose to model the drift as a nonlinear reduced-order model, such as a deep network, and enforce the matching to the target distribution at terminal time either strictly or approximately using the Wasserstein metric. The resulting saddle-point problem can be solved by an effective numerical algorithm that leverages the excellent representation power of deep networks and fast automatic differentiation for this challenging high-dimensional control problem. A variety of numerical experiments were conducted to demonstrate the performance of our method.
|
|
11:40-12:00, Paper FrA22.6 | |
>Optimal Mass Transport Over the Euler Equation (I) |
|
Yan, Charlie | University of California Santa Cruz |
Nodozi, Iman | University of California, Santa Cruz |
Halder, Abhishek | Iowa State University |
Keywords: Stochastic optimal control, Stochastic systems, Uncertain systems
Abstract: We consider the finite horizon optimal steering of the joint state probability distribution subject to the angular velocity dynamics governed by the Euler equation. The problem and its solution amounts to controlling the spin of a rigid body via feedback, and is of practical importance, for example, in angular stabilization of a spacecraft with stochastic initial and terminal states. We clarify how this problem is an instance of the optimal mass transport (OMT) problem with bilinear prior drift. We deduce both static and dynamic versions of the Eulerian OMT, and provide analytical and numerical results for the synthesis of the optimal controller.
|
|
FrA23 |
Orchid Junior 4211 |
Formal Methods for Time-Critical Decision Making and Control |
Invited Session |
Chair: Lindemann, Lars | University of Southern California |
Co-Chair: Vasile, Cristian Ioan | Lehigh University |
Organizer: Lindemann, Lars | University of Southern California |
Organizer: Vasile, Cristian Ioan | Lehigh University |
Organizer: Belta, Calin | Boston University |
Organizer: Dimarogonas, Dimos V. | KTH Royal Institute of Technology |
|
10:00-10:20, Paper FrA23.1 | |
>Diagnosis of Time-Sensitive Failures in Timed Discrete-Event Systems with Metric Interval Temporal Logics (I) |
|
Dong, Weijie | Shanghai Jiao Tong University |
Li, Shaoyuan | Shanghai Jiao Tong University |
Yin, Xiang | Shanghai Jiao Tong University |
Keywords: Discrete event systems, Automata, Fault diagnosis
Abstract: In this paper, we address the problem of failure diagnosis in timed discrete-event systems modeled by timed automata. While existing works on this topic typically focus on failures modeled as particular events, many complex applica- tions, especially time-critical systems, require the ability to identify time-sensitive failures associated with real-time information rather than just the occurrence of events at any time. To address this challenge, we propose the use of metric interval temporal logic (MITL) with continuous semantics on Boolean signals to formally describe time-sensitive failures. We introduce a novel concept called time-sensitive diagnosability (TS-diagnosability) to characterize whether or not any violation of the MITL task (i.e., failure) can be determined within a finite time elapsing. Furthermore, we provide a necessary and sufficient condition for verifying TS-diagnosability. Our results offer a more general framework for failure diagnosis of timed discrete-event systems
|
|
10:20-10:40, Paper FrA23.2 | |
>Model-Free Reinforcement Learning for Spatiotemporal Tasks Using Symbolic Automata (I) |
|
Balakrishnan, Anand | University of Southern California |
Jaksic, Stefan | Austrian Institute of Technology |
Aguilar, Edgar | Austrian Institute of Technology |
Nickovic, Dejan | AIT Austrian Institute of Technology GmbH |
Deshmukh, Jyotirmoy | University of Southern California |
Keywords: Learning, Formal Verification/Synthesis, Markov processes
Abstract: Reinforcement learning (RL) is a popular paradigm for synthesizing controllers in environments modeled as Markov Decision Processes (MDPs). The RL formulation assumes that users define local rewards that depend only on the current state (and action), and learning algorithms seek to find control policies that maximize cumulative rewards along system trajectories. An implicit assumption in RL is that policies that maximize cumulative rewards are desirable as they meet the intended control objectives. However, most control objectives are emph{global} properties of system trajectories, and meeting them with local rewards requires tedious, manual and error-prone process of hand-crafting the rewards. We propose a new algorithm for automatically inferring local rewards from high-level task objectives expressed in the form of emph{symbolic automata} (SA); a symbolic automaton is a finite state machine where edges are labeled with symbolic predicates over the MDP states. SA subsume many popular formalisms for expressing task objectives, such as discrete-time versions of Signal Temporal Logic (STL). We assume that a model-free RL setting, i.e., we assume emph{no prior knowledge} of the system dynamics. We give theoretical results that establish that an optimal policy learned using our shaped rewards also maximizes the probability of satisfying the given SA-based control objective. Our approach is empirically compared with other RL methods that use temporal logic and automata-based control objectives, and evaluate them based on training convergence time and the probability of satisfying finite horizon control objectives.
|
|
10:40-11:00, Paper FrA23.3 | |
>Robustness Measures and Monitors for Time Window Temporal Logic (I) |
|
Ahmad, Ahmad | Boston University |
Vasile, Cristian Ioan | Lehigh University |
Tron, Roberto | Boston University |
Belta, Calin | Boston University |
Keywords: Formal Verification/Synthesis
Abstract: Temporal logics (TLs) have been widely used to formalize interpretable tasks for cyber-physical systems. Time Window Temporal Logic (TWTL) has been recently proposed as a specification language for dynamical systems. In particular, it can easily express robotic tasks, and it allows for efficient, automata-based verification and synthesis of control policies for such systems. In this paper, we define two quantitative semantics for this logic, and two corresponding monitoring algorithms, which allow for real-time quantification of satisfaction of formulas by trajectories of discrete-time systems. We demonstrate the new semantics and their runtime monitors on numerical examples.
|
|
11:00-11:20, Paper FrA23.4 | |
>Efficient Control Synthesis under Asynchronous Temporal Robustness Constraints (I) |
|
Yu, Xinyi | University of Southern California |
Yin, Xiang | Shanghai Jiao Tong University |
Lindemann, Lars | University of Southern California |
Keywords: Formal Verification/Synthesis, Discrete event systems
Abstract: In time-critical systems, such as air traffic control systems, it is crucial to design control policies that are robust to timing uncertainty. Recently, the notion of asynchronous temporal robustness (ATR) was proposed to capture the robustness of a system trajectory against individual time shifts in its sub-trajectories. In a multi-robot system, this may correspond to individual robots being delayed or early. Control synthesis under ATR constraints is challenging and has not yet been addressed. In this paper, we propose a efficient control synthesis method under ATR constraints which are defined with respect to simple safety or complex signal temporal logic specifications. Given an ATR bound, we compute a sequence of control inputs so that the specification is satisfied by the system as long as each sub-trajectory is shifted not more than the ATR bound. We avoid combinatorially exploring all shifted sub-trajectories by first identifying redundancy between them. We capture this insight by the notion of instant-shift pair sets, and then propose an optimization program that enforces the specification only over the instant-shift pair sets. We show soundness and completeness of our method and analyze its computational complexity. Finally, we present various illustrative case studies.
|
|
11:20-11:40, Paper FrA23.5 | |
>Signal Temporal Logic Meets Convex-Concave Programming: A Structure-Exploiting SQP Algorithm for STL Specifications (I) |
|
Takayama, Yoshinari | CentraleSupelec |
Hashimoto, Kazumune | Osaka University |
Ohtsuka, Toshiyuki | Kyoto Univ |
Keywords: Formal Verification/Synthesis, Optimization algorithms, Optimal control
Abstract: This study considers the control problem with signal temporal logic (STL) specifications. Prior works have adopted smoothing techniques to address this problem within a feasible time frame and solve the problem by applying sequential quadratic programming (SQP) methods naively. However, one of the drawbacks of this approach is that solutions can easily become trapped in local minima that do not satisfy the specification. In this study, we propose a new optimization method, termed CCP-based SQP, based on the convex-concave procedure (CCP). Our framework includes a new robustness decomposition method that decomposes the robustness function into a set of constraints, resulting in a form of difference of convex (DC) program that can be solved efficiently. We solve this DC program sequentially as a quadratic program by only approximating the disjunctive parts of the specifications. Our experimental results demonstrate that our method has a superior performance compared to the state-of-the-art SQP methods in terms of both robustness and computational time.
|
|
11:40-12:00, Paper FrA23.6 | |
>Energy-Constrained Active Exploration under Incremental-Resolution Symbolic Perception (I) |
|
Kamale, Disha | Lehigh University |
Haesaert, Sofie | Eindhoven University of Technology |
Vasile, Cristian Ioan | Lehigh University |
Keywords: Formal Verification/Synthesis, Autonomous robots
Abstract: We consider the problem of autonomous exploration in search of targets while respecting a fixed energy budget. The robot is equipped with an incremental-resolution symbolic perception module wherein the perception of targets in the environment improves as the robot's distance from targets decreases. We assume no prior information about the number of targets, their locations, and possible distribution within the environment. This work proposes a novel decision-making framework for the resulting constrained sequential decision-making problem by first converting it into a reward maximization problem on a product graph computed offline. It is then solved online as a Mixed-Integer Linear Program (MILP) where the knowledge about the environment is updated at each step, combining automata-based and MILP-based techniques. We demonstrate the efficacy of our approach with the help of a case study and present empirical evaluation in terms of expected regret. Furthermore, the runtime performance shows that online planning can be efficiently performed for moderately-sized grid environments.
|
|
FrA24 |
Orchid Main 4201AB |
Event-Triggered and Self-Triggered Control III |
Invited Session |
Chair: Diagne, Mamadou | University of California San Diego |
Co-Chair: Yang, Feisheng | Northwestern Polytechnical University |
Organizer: Heemels, W.P.M.H. | Eindhoven University of Technology |
Organizer: Hirche, Sandra | Technische Universität München |
Organizer: Nowzari, Cameron | George Mason University |
|
10:00-10:20, Paper FrA24.1 | |
>Data-Driven Self-Triggered Control for Linear Networked Control Systems (I) |
|
Xin, Wang | Beijing Institute of Technology |
Li, Yifei | Beijing Institute of Technology |
Sun, Jian | Beijing Institute of Technology |
Wang, Gang | Beijing Institute of Technology |
Chen, Jie | Beijing Institute of Technology |
Dou, Lihua | Beijing Institute of Technology |
Keywords: Networked control systems, Data driven control, Sampled-data control
Abstract: This paper considers data-driven control of unknown linear discrete-time systems under a self-triggered transmission scheme. While self-triggered control has received much attention in the literature, its design and implementation typically require explicit model knowledge. Due to the difficulties in obtaining accurate models and the abundance of data in applications, this paper proposes a novel data-driven self-triggered control scheme for unknown systems. To this end, we begin by presenting a model-based self-triggered scheme (STS) in form of quadratic matrix inequalities, on the basis of an equivalent switched system representation. Combining the model-based triggering law and a data-based system representation, a data-driven STS is developed leveraging pre-collected input-state data for predicting the next transmission instant while ensuring system stability. A data-based method for co-designing the controller gain and the triggering matrix is then provided. Finally, a numerical simulation showcases the efficacy of STS in reducing transmissions as well as practicality of the proposed co-design methods.
|
|
10:20-10:40, Paper FrA24.2 | |
>On the Digital Event-Based Implementation of a Glucose Regulator Via Subcutaneous Insulin Infusion (I) |
|
Di Ferdinando, Mario | University of L'Aquila |
Di Gennaro, Stefano | University of L'Aquila |
Borri, Alessandro | CNR-IASI |
Pola, Giordano | University of L'Aquila |
Pepe, Pierdomenico | University of L' Aquila |
Keywords: Biomedical, Sampled-data control, Nonlinear systems
Abstract: In this paper, an event-based quantized sampled-data control strategy is proposed for the plasma glucose regulation problem in Type 2 diabetic patients. In particular, the proposed event-triggered digital glucose regulator is designed by exploiting a nonlinear time-delay model of the glucose-insulin regulatory system which takes into account the subcutaneous infusion of insulin. It is proved that the provided quantized sampled-data glucose controller, updated via a proposed event-based mechanism, guarantees the semi-global practical stability property of the related closed--loop tracking error system, with arbitrarily small steady--state tracking error. The stabilization in the sample--and--hold sense theory is used as a tool to prove the results. An approximation scheme based on first--order splines is used in order to cope with the problem of the possible non--availability in the buffer of the value of the system variables at some past times which are needed for the implementation of the proposed digital controller. The possible non-uniform quantization of the input/output channels as well as the case of time--varying sampling periods are included in the theory here developed. The validation of the proposed glucose control strategy is carried out via simulations.
|
|
10:40-11:00, Paper FrA24.3 | |
>Event-Triggered Control for Hamiltonian-Based Flexible-Joints Robots |
|
Zhang, Qi | Qufu Normal University |
Sun, Weiwei | Qufu Normal University |
Ding, Lusong | Qufu Normal University Institute of Automation |
Li, Yongshu | Qufu Normal University,School of Engineering |
Keywords: Robotics, Nonlinear systems, Network analysis and control
Abstract: This paper focuses on the event-triggered tracking control problem for Hamiltonian-based flexible-joints robots. Based on Hamiltonian theory and the delay system approach, an event-triggered modular control strategy is proposed to guarantee that the link and motor generalized position can track the target signal asymptotically while reducing the waste of transmission resources. The modular controller designed in this paper takes fully into account the structural characteristics of the flexible-joints robots. Moreover, the difficulties of tracking control and event-triggered control caused by the high coupling of Hamiltonian systems are overcome in the design process. This extends the existing theoretical results for flexible-joints robots and effectively improves energy efficiency. The validity of the proposed strategy is verified by a simulation example of a flexible joint robot.
|
|
11:00-11:20, Paper FrA24.4 | |
>Self-Triggered Boundary Control of a Class of Reaction-Diffusion PDEs (I) |
|
Rathnayake, Bhathiya | Student (University of California San Diego) |
Diagne, Mamadou | University of California San Diego |
Keywords: Backstepping, Hybrid systems, Stability of linear systems
Abstract: This paper provides a novel self-triggered boundary control (STBC) strategy for a class of reaction-diffusion PDEs with Robin actuation using infinite-dimensional backstepping boundary control. Our goal is to offer a solution for the continuous monitoring of triggering functions in conventional event-triggered control. We propose a method for converting a certain class of continuous-time dynamic event-triggers that require continuous monitoring to self-triggers that proactively compute the time of the next event at the current event time using the knowledge of the available system states and dynamics. We achieve this by designing a positively and uniformly lower-bounded function which, when evaluated at the current event time, outputs the waiting time until the next event. The control input is updated only at events indicated by the self-trigger and is applied in a zero-order hold fashion between two events. We establish the closed-loop system well-posedness under the proposed STBC approach. Furthermore, we prove that the global L^2-exponential convergence to zero under continuous-time event-triggered boundary control (CETBC) is preserved under the proposed STBC approach. We provide a simulation result that validates the theoretical claims.
|
|
11:20-11:40, Paper FrA24.5 | |
>Predefined-Time Distributed Optimal Consensus for Euler–Lagrangian Systems Based on Dynamic Event-Triggered Mechanism (I) |
|
Yang, Feisheng | Northwestern Polytechnical University |
Liu, Jiaming | Northwestern Polytechnical University |
Ma, Qian | Nanjing University of Science and Technology |
Keywords: Distributed control, Optimal control, Cooperative control
Abstract: It is a challenging problem to achieve fast distributed optimal consensus for Euler–Lagrangian (EL) systems meanwhile economizing communication resources. To solve the problem, a novel predefined-time distributed optimal consensus strategy for EL systems is proposed by applying time-base generator (TBG) and dynamic event-triggered mechanism, which can reach the optimal consensus in a completely distributed manner. It is proven that the algorithm can converge in predefined time by Lyapunov energy function and Zeno behavior is avoided. A dynamic event-triggered method is designed which event-triggered thresholds are replaced by dynamic variables. The numerical simulation is given to show the effectiveness and superiority of the algorithm.
|
|
11:40-12:00, Paper FrA24.6 | |
>Event-Triggered Stabilization of Parabolic PDEs by Switching (I) |
|
Kang, Wen | Beijing Institute of Technology |
Fridman, Emilia | Tel-Aviv Univ |
Zhang, Jing | Beijing Institute of Technology |
Liu, Chuan-Xin | University of Science and Technology Beijing |
Keywords: Distributed parameter systems, Stability of nonlinear systems, Lyapunov methods
Abstract: Although switching-based stabilization of 1D parabolic systems was investigated by employing one actuator moving in spatial domain in our recent paper [18], this method increases the system cost since actuator and sensor switching happens at fixed time regardless of whether the switching is necessary or not. To further reduce operating and production cost, in the present paper, switching-based dynamic event-triggered control law is studied to stabilize the parabolic PDE systems via output-dependent switching law. Constructive exponential stability conditions are established by using Lyapunov method. A numerical example shows the effectiveness of the proposed methods.
|
|
FrA25 |
Lotus Junior 4DE |
Navigating Complexity: New Approaches for Discrete Event Systems |
Invited Session |
Chair: Giua, Alessandro | University of Cagliari |
Co-Chair: Seatzu, Carla | Univ. of Cagliari |
Organizer: Giua, Alessandro | University of Cagliari |
Organizer: Seatzu, Carla | Univ. of Cagliari |
|
10:00-10:20, Paper FrA25.1 | |
>Transformational Supervisor Localization |
|
Thuijsman, Sander | Eindhoven University of Technology |
Cai, Kai | Osaka Metropolitan University |
Reniers, Michel | Eindhoven University of Technology |
Keywords: Supervisory control, Discrete event systems, Automata
Abstract: Supervisor localization can be applied to distribute a monolithic supervisor into local supervisors. Performing supervisor localization can be computationally costly. In this work, we consider systems that evolve over time. We study how to reuse the results from a previous supervisor localization, to more efficiently compute local supervisors when the system is adapted. We call this approach transformational supervisor localization, and present algorithms for the procedure. The efficiency of the procedure is experimentally evaluated.
|
|
10:20-10:40, Paper FrA25.2 | |
>Opacity from Observers with a Bounded Memory |
|
Wintenberg, Andrew | The University of Michigan, Ann Arbor |
Lafortune, Stephane | Univ. of Michigan |
Ozay, Necmiye | Univ. of Michigan |
Keywords: Discrete event systems
Abstract: Opacity is an information-flow property capturing privacy from observers that are aware of a system’s dynamics. The potential for an observer with perfect recall to reason about long histories of the system poses a challenge for opacity verification. In this paper, we address this challenge by proposing a new notion of opacity over automata, called bounded memory opacity, with respect to an observer with a bounded memory. We show that verifying this weaker notion of opacity has reduced computational complexity compared to general opacity (co-NP vs. PSPACE). Furthermore, we present a corresponding verification algorithm using an encoding to the Boolean satisfiability problem (SAT). We demonstrate this approach on randomly generated automata as well as a web server load-hiding example.
|
|
10:40-11:00, Paper FrA25.3 | |
>Decentralized State Estimation Via Breadth-First Search through Partially Ordered Observation Sequences (I) |
|
Sun, Dajiang | Xidian University |
Hadjicostis, Christoforos N. | University of Cyprus |
Li, Zhiwu | Xidian University |
Keywords: Discrete event systems, Automata, Estimation
Abstract: We investigate the state estimation problem under a decentralized observation architecture. More specifically, we consider a discrete event system, modeled by a nondeterministic finite automaton, whose behavior is partially observed and recorded at a set of observation sites with distinct capabilities. When prompted, these observation sites send their sequences of observations to a coordinator that fuses and analyzes this information to estimate the specific system states of interest (current- and initial-states). The notion of S-builder is introduced to systematically infer possible (totally ordered) sequences of observations and an algorithm is proposed for constructing a synchronizer in a breadth-first search manner to efficiently perform current-state estimation. With slight extensions, the synchronizer construction algorithm can be also applied towards initial-state estimation.
|
|
11:00-11:20, Paper FrA25.4 | |
>Data-Informativity for Data-Driven Supervisory Control of Discrete-Event Systems (I) |
|
Ohtsuka, Tomofumi | Kyoto University |
Cai, Kai | Osaka Metropolitan University |
Kashima, Kenji | Kyoto University |
Keywords: Discrete event systems, Supervisory control, Data driven control
Abstract: In this paper we develop a data-driven approach for supervisory control of discrete-event systems (DES). We consider a setup in which models of DES to be controlled are unknown, but a set of data concerning the behaviors of DES is available. We propose a new concept of data-informativity, which captures the notion that the available data set contains sufficient information such that a valid supervisor may be constructed for a family of DES models that all can generate the data set. We then characterize data-informativity with a necessary and sufficient condition, based on which we design an algorithm for its verification. Moreover, if the data set fails to be informative, we propose two related new concepts of limited data-informativity and informatizability. Their characterization conditions and verification algorithms are also presented.
|
|
11:20-11:40, Paper FrA25.5 | |
>Logical and Probabilistic Aspects of State Estimation for Markovian Systems (I) |
|
Lefebvre, Dimitri | University Le Havre |
Seatzu, Carla | Univ. of Cagliari |
Hadjicostis, Christoforos N. | University of Cyprus |
Giua, Alessandro | University of Cagliari |
Keywords: Discrete event systems, Automata, Markov processes
Abstract: This paper is about state estimation in a class of labeled timed probabilistic automata. In detail, we consider continuous time Markov processes where the occurrence of some transitions produces observable events. Such observations can be used to update and refine the state estimation. In this setting, we discuss how a logical state estimation approach can be used to characterize the probabilistic state estimation whenever a new event is observed or when the system evolves without producing new observations (silent closure). The main results of the paper show that the final behaviour, as the silent closure goes to infinity, cannot be characterized only in terms of the graphical structure of the underlying automaton but also depends on the values of the firing rates.
|
|
11:40-12:00, Paper FrA25.6 | |
>On the Reachability Space and Deadlock-Freeness in Flexible Nets (I) |
|
Julvez, Jorge | University of Zaragoza |
Keywords: Petri nets, Discrete event systems, Modeling
Abstract: Deadlock-freeness is a basic property of dynamical systems that ensures that at least one process of the system can operate indefinitely. Given that a system is deadlock-free if at any reachable state there is at least one process that can operate, the reachability space, i.e. the set of states that can be reached, and deadlock-freeness are closely related. This paper focuses on some fundamental properties of the reachability space of Flexible Nets, a modeling formalism that can easily account for uncertain parameters. After showing that the reachability space is convex, a sufficient condition for deadlock-freeness is derived.
|
|
FrA26 |
Orchid Main 4301AB |
Autonomous Robots |
Regular Session |
Chair: Markdahl, Johan | University of Luxembourg |
Co-Chair: Arslan, Omur | Eindhoven University of Technology |
|
10:00-10:20, Paper FrA26.1 | |
>Adaptive Headway Motion Control and Motion Prediction for Safe Unicycle Motion Design |
|
Isleyen, Aykut | Eindhoven University of Technology |
Van De Wouw, Nathan | Eindhoven University of Technology |
Arslan, Omur | Eindhoven University of Technology |
Keywords: Autonomous robots, Nonholonomic systems, Feedback linearization
Abstract: Differential drive robots that can be modeled as a kinematic unicycle are a standard mobile base platform for many service and logistics applications. Safe and smooth autonomous motion around obstacles is a crucial skill for unicycle robots to perform diverse tasks in complex environments. A classical control approach for unicycle control is feedback linearization using a headway point at a fixed headway distance in front of the unicycle. The unicycle headway control brings the headway point to a desired goal location by embedding a linear headway reference dynamics, which often results in an undesired offset for the actual unicycle position. In this paper, we introduce a new unicycle headway control approach with an adaptive headway distance that overcomes this limitation, i.e., when the headway point reaches the goal the unicycle position is also at the goal. By systematically analyzing the closed-loop unicycle motion under the adaptive headway controller, we design analytical feedback motion prediction methods that bound the closed-loop unicycle position trajectory and so can be effectively used for safety assessment and safe unicycle motion design around obstacles. We present an application of adaptive headway motion control and motion prediction for safe unicycle path following around obstacles in numerical simulations.
|
|
10:20-10:40, Paper FrA26.2 | |
>Min-Time Coverage in Constricted Environments with Arbitrary Guidepath Networks |
|
Kim, Young-In | ISyE, Georgia Tech |
Reveliotis, Spyros | Georgia Institute of Technology |
Keywords: Autonomous robots, Networked control systems, Optimization
Abstract: In a recent research program, we have undertaken the investigation of robotic traffic management problems arising when a fleet of networked mobile robots is employed in the support of certain coverage tasks that take place in physically constricted environments. But our past investigation of these problems is restricted to the case where the guidepath networks supporting the robot traffic have a dendritic topology. In the current work, we extend the investigation of the considered problems to the case where the underlying guidepath networks have an arbitrary topology. We provide (i) detailed descriptions of the considered problems in this new operational setting, (ii) analytical characterizations of these problems that take the form of integer programming formulations, and (iii) strong combinatorial relaxations for the derived formulations that are applicable to larger problem instances. A numerical experiment presented in the last part of the manuscript demonstrates and assesses the efficacy and the tractability of the analytical developments. We also notice that the undertaken extension of the past results is a nontrivial task, for the reasons that are explained in the manuscript.
|
|
10:40-11:00, Paper FrA26.3 | |
>Swarm Bug Algorithms for Path Generation in Unknown Environments |
|
Johansson, Alexander | KTH |
Markdahl, Johan | The Swedish Defence Research Agency |
Keywords: Autonomous robots, Agents-based systems
Abstract: In this paper, we consider the problem of a swarm traveling between two points as fast as possible in an unknown environment cluttered with obstacles. Potential applications include search-and-rescue operations where damaged environments are typical. We present swarm generalizations, called SwarmCom, SwarmBug1, and SwarmBug2, of the classical path generation algorithms Com, Bug1, and Bug2. These algorithms were developed for unknown environments and require low computational power and memory storage, thereby freeing up resources for other tasks. We show the upper bound of the worst-case travel time for the first agent in the swarm to reach the target point for SwarmBug1. For SwarmBug2, we show that the algorithm underperforms in terms of worst-case travel time compared to SwarmBug1. For SwarmCom, we show that there exists a trivial scene for which the algorithm will not halt, and it thus has no performance guarantees. Moreover, by comparing the upper bound of the travel time for SwarmBug1 with a universal lower bound for any path generation algorithm, it is shown that in the limit when the number of agents in the swarm approaches infinity, no other algorithm has strictly better worst-case performance than SwarmBug1 and the universal lower bound is tight.
|
|
11:00-11:20, Paper FrA26.4 | |
>Abstraction-Based Motion Coordination Control for Multi-Robot Systems |
|
Pan, Zhuo-Rui | Dalian University of Technology |
Ren, Wei | Dalian University of Technology |
Sun, Xi-Ming | Dalian University of Technology |
Keywords: Autonomous robots, Optimal control, Distributed control
Abstract: This paper studies the motion coordination control problem for multiple mobile robots under a common workspace and reach-avoid tasks. Using abstraction-based techniques, we combine the offline and online control methods to propose a distributed motion coordination control strategy. In the offline control strategy, we partition the workspace to derive the graph for the offline planning, and construct the symbolic abstraction for each robot to design the individual controller offline. In the online control strategy, we provide a detection mechanism to check the existence of the potential robot collision, and implement the constructed symbolic abstraction and graph-searching techniques to resolve the robot collision. The combination of the offline and online control strategies results in the overall motion coordination control strategy for all robots.
|
|
11:20-11:40, Paper FrA26.5 | |
>Moving Target Estimation and Active Tracking in Multi-Robot Systems |
|
Xu, Jie | University of California, Riverside |
Zhu, Pengxiang | University of California, Riverside |
Zhang, Yanyu | University of California, Riverside |
Ren, Wei | University of California, Riverside |
Keywords: Autonomous robots, Sensor fusion, Kalman filtering
Abstract: In this paper, we propose a comprehensive solution for 3-D active target tracking with multiple robots in a fully distributed setting. Here multiple robots cooperatively estimate their own states and the target’s state and actively plan their motions to achieve better estimation of the target. For cooperative localization and target state estimation, each robot maintains a state vector consisting of its own state, the target’s state, and its own cloned history states. The challenge of localizing moving robots in 3-D is addressed by using multirobot cooperative visual-inertial odometry algorithm, which improves the estimation accuracy by using environmental common feature measurements. Each robot’s target measurement (if available) and its neighbors’ target estimators are then exploited for estimation updates. To preserve and update the correlations between the target and robot states while limiting the influence of bad target estimates on localization accuracy, the Schmidt-Kalman Filter framework is adopted. For motion planning, a gradient-based approach that uses differentiable field-of-view and potential functions is employed to achieve efficient and accurate active target tracking while avoiding collisions and maintaining communication connectivity. Numerous simulations show that our proposed algorithm provides an accurate and efficient solution for cooperative localization and active target tracking.
|
|
11:40-12:00, Paper FrA26.6 | |
>An Integral Sliding–Mode–based Robust Interval Predictive Control for Perturbed Unicycle Mobile Robots |
|
Ríos, Héctor | Tecnológico Nacional De México/I.T. La Laguna |
Mera, Manuel | Esime Upt Ipn |
Raïssi, Tarek | Conservatoire National Des Arts Et Métiers |
Efimov, Denis | Inria |
Keywords: Autonomous robots, Variable-structure/sliding-mode control, Constrained control
Abstract: This paper contributes to the design of a robust control strategy for the trajectory tracking problem in perturbed unicycle mobile robots. The proposed strategy comprises the design of a robust control law, which is based on an Integral Sliding–Mode Control (ISMC) approach together with an interval predictor–based state–feedback controller and a Model Predictive Control (MPC) scheme. The robust controller deals with some perturbations in the kinematic model, and with state and input constraints that are related to restrictions on the workspace and saturated actuators, respectively. The proposed approach guarantees the exponential convergence to zero of the tracking error. Furthermore, the performance of the proposed approach is validated through some simulations.
|
|
FrB01 |
Melati Junior 4010A-4111 |
Learning, Optimization, and Game Theory IV |
Invited Session |
Chair: Zhang, Kaiqing | University of Maryland |
Co-Chair: Vamvoudakis, Kyriakos G. | Georgia Inst. of Tech |
Organizer: Doan, Thinh T. | Virginia Tech |
Organizer: Sayin, Muhammed Omer | Bilkent University |
Organizer: Vamvoudakis, Kyriakos G. | Georgia Inst. of Tech |
Organizer: Zhang, Kaiqing | University of Maryland |
|
13:30-13:50, Paper FrB01.1 | |
>Lyapunov-Based Long Short-Term Memory (Lb-LSTM) Neural Network-Based Control |
|
Griffis, Emily | University of Florida |
Patil, Omkar Sudhir | University of Florida |
Bell, Zachary I. | Air Force |
Dixon, Warren E. | University of Florida |
Keywords: Adaptive control, Neural networks, Stability of nonlinear systems
Abstract: Recurrent neural networks (RNNs) are a dynamic mapping that can capture time-varying, accumulative effects in a sequence that static, feedforward neural networks (NNs) cannot. Long short-term memory (LSTM) NNs are a type of RNNs that have gained recent popularity because the cell structure allows them to retain long-term information more efficiently than traditional RNNs. Existing results develop LSTM-based controllers to compensate for uncertainties in nonlinear systems. However, these results use discrete-time LSTMs with offline-trained weights. In this paper, a Lyapunov-based LSTM controller is developed for general Euler-Lagrange systems. Specifically, an Lb-LSTM is implemented in the control design to adaptively estimate uncertain model dynamics, where the weight estimates of the LSTM cell are updated using Lyapunov-based adaptation laws. This allows the LSTM cell to adapt to system uncertainties without requiring offline training. A Lyapunov-based stability analysis yields uniform ultimate boundedness (UUB) of the tracking errors and LSTM state and weight estimation errors. Simulations indicate the developed Lb-LSTM-based controller yielded significant improvement in tracking and function approximation performance when compared to several DNN examples.
|
|
13:50-14:10, Paper FrB01.2 | |
>High-Confidence Barrier-Certified Control Design Using Goal-Oriented Scenario Optimization and Experience Replay Model Learning (I) |
|
Marvi, Zahra | University of Minnesota |
Kiumarsi, Bahare | Michigan State University |
Modares, Hamidreza | Michigan State University |
Keywords: Learning, Optimization, Uncertain systems
Abstract: This paper presents a probabilistic framework for the safe control of linear systems under parametric uncertainties. To this end, a two-layer learning-enabled controller is presented that unifies the experience-replay model learning and the scenario-based optimization. The inner loop leverages the scenario optimization to impose probabilistic stability and safety specifications through sampling from a control Lyapunov function and a control barrier function, respectively. Each sample represents a plausible system dynamics realization within the range of the uncertainties. To quantify the model uncertainty and, thus, to facilitate a proactive and goal-oriented sampling of safety and stability constraints, an experience replay-based model learning is presented in the outer loop. The exponentially fast convergent guarantees of the presented approach and the quantification of the exponential rate using the collected data allow us to quantify the ambiguity set for the system parameters based on the data informativeness. The quantified modeling error acts as a vanishing perturbation to the true dynamics, from which samples can be taken at a specific frequency to solve an optimization problem in the inner loop. The presented approach provides safety and stability guarantees with high probability, even during learning. Simulation is used to depict the efficacy of the proposed approach.
|
|
14:10-14:30, Paper FrB01.3 | |
>Quality of Non-Convergent Best Response Processes in Multi-Agent Systems through Sink Equilibria (I) |
|
Konda, Rohit | UC Santa Barbara |
Chandan, Rahul | Amazon.com |
Marden, Jason R. | University of California, Santa Barbara |
Keywords: Game theory, Optimization, Autonomous systems
Abstract: Examining the behavior of multi-agent systems is vitally important to many emerging distributed applications - game theory has emerged as a powerful tool set in which to do so. The main approach of game-theoretic techniques is to model agents as players in a game, and predict the emergent behavior through the relevant Nash equilibria. The virtue from this viewpoint is that by assuming that self-interested decision-making processes lead to Nash equilibrium, system behavior can then be captured by Nash equilibrium without studying the decision-making processes explicitly. This approach has seen success in a wide variety of domains, such as sensor coverage, traffic networks, auctions, and network coordination. However, in many other problem settings, Nash equilibria are not necessarily guaranteed to exist or emerge from self-interested processes. Thus the main focus of the paper is on the study of sink equilibria, which are defined as the attractors of these decision-making processes. By classifying system outcomes through a global objective function, we can analyze the resulting approximation guarantees that sink equilibria have for a given game. Our main result is an approximation guarantee on the sink equilibria through defining an introduced metric of misalignment, which captures how uniform agents are in their self-interested decision making. Overall, sink equilibria are naturally occurring in many multi-agent contexts, and we display our results on their quality with respect to two practical problem settings.
|
|
14:30-14:50, Paper FrB01.4 | |
>Asynchronous Distributed Optimization Via ADMM with Efficient Communication (I) |
|
Rikos, Apostolos I. | KTH Royal Institute of Technology |
Jiang, Wei | Aalto University, Finland |
Charalambous, Themistoklis | University of Cyprus |
Johansson, Karl H. | KTH Royal Institute of Technology |
Keywords: Optimization, Optimization algorithms, Agents-based systems
Abstract: In this paper, we focus on an asynchronous distributed optimization problem. In our problem, each node is endowed with a convex local cost function, and is able to communicate with its neighbors over a directed communication network. Furthermore, we assume that the communication channels between nodes have limited bandwidth, and each node suffers from processing delays. We present a distributed algorithm which combines the Alternating Direction Method of Multipliers (ADMM) strategy with a finite time quantized averaging algorithm. In our proposed algorithm, nodes exchange quantized valued messages and operate in an asynchronous fashion. More specifically, during every iteration of our algorithm each node (i) solves a local convex optimization problem (for the one of its primal variables), and (ii) utilizes a finite-time quantized averaging algorithm to obtain the value of the second primal variable (since the cost function for the second primal variable is not decomposable). We show that our algorithm converges to the optimal solution at a rate of O(1/k) (where k is the number of time steps) for the case where the local cost function of every node is convex and not-necessarily differentiable. Finally, we demonstrate the operational advantages of our algorithm against other algorithms from the literature.
|
|
14:50-15:10, Paper FrB01.5 | |
>Boosting Exploration in Actor-Critic Algorithms by Incentivizing Plausible Novel States (I) |
|
Banerjee, Chayan | Queensland University of Technology |
Chen, Zhiyong | The University of Newcastle |
Noman, Nasimul | The University of Newcastle |
Keywords: Learning, Stochastic optimal control, Neural networks
Abstract: Improvement of exploration and exploitation using more efficient samples is a critical issue in reinforcement learning algorithms. A basic strategy of a learning algorithm is to facilitate indiscriminate exploration of the entire environment state space, as well as to encourage exploration of rarely visited states rather than frequently visited ones. Under this strategy, we propose a new method to boost exploration through an intrinsic reward, based on the measurement of a state's novelty and the associated benefit of exploring the state, collectively called plausible novelty. By incentivizing exploration of plausible novel states, an actor-critic (AC) algorithm can improve its sample efficiency and, consequently, its training performance. The new method is verified through extensive simulations of continuous control tasks in MuJoCo environments, using a variety of prominent off-policy AC algorithms.
|
|
15:10-15:30, Paper FrB01.6 | |
>Risk-Sensitive RL Using Sampling-Based Expectation-Maximization (I) |
|
Noorani, Erfaun | University of Maryland College Park |
Baras, John S. | University of Maryland |
Johansson, Karl H. | KTH Royal Institute of Technology |
Keywords: Machine learning, Learning
Abstract: There is a need for robust Reinforcement Learning (RL) algorithms that can cope with model misspecification, parameter uncertainty, disturbances, etc. Risk-sensitive methods offer an approach to developing robust RL algorithms by hedging against undesirable outcomes in a probabilistic manner. The Probabilistic Graphical Model (PGM) framework offers systematic exploration for risk-sensitive RL. In this paper, we bridge the Markov Decision Process (MDP) and the PGM frameworks. We exploit the equivalence of optimizing a certain risk-sensitive criterion in the MDP formalism with optimizing a log-likelihood objective in the PGM formalism. By utilizing this equivalence, we offer an approach for developing risk-sensitive algorithms by leveraging the PGM framework. We explore the Expectation-Maximization (EM) algorithm under the PGM formalism. We show that risk-sensitive policy gradient methods can be obtained by applying sampling-based approaches to the EM algorithm, e.g., Monte-Carlo EM, with the log-likelihood. We show that Monte-Carlo EM leads to a risk-sensitive Monte-Carlo policy gradient algorithm. Our simulations illustrate the risk-sensitive nature of the resulting algorithm.
|
|
FrB02 |
Orchid Main 4202-4303 |
Data-Driven Verification and Control of Cyber-Physical Systems II |
Invited Session |
Chair: Jungers, Raphaël M. | University of Louvain |
Co-Chair: Lavaei, Abolfazl | Newcastle University |
Organizer: Lavaei, Abolfazl | Newcastle University |
Organizer: Jungers, Raphaël M. | University of Louvain |
Organizer: Abate, Alessandro | University of Oxford |
|
13:30-13:50, Paper FrB02.1 | |
>Data-Driven Synthesis of Safety Controllers Via Multiple Control Barrier Certificates |
|
Nejati, Ameneh | Technical University of Munich (TUM) |
Zamani, Majid | University of Colorado Boulder |
Keywords: Discrete event systems
Abstract: This work proposes a data-driven framework to synthesize safety controllers for nonlinear systems with finite input sets and unknown mathematical models. The proposed scheme leverages new notions of multiple control barrier certificates (M-CBC) and provides controllers ensuring the safety of systems with confidence 1. While there may not exist a common control barrier certificate with a fixed template, our proposed technique adaptively partitions the state set to potentially find M-CBC of the same template for different regions. In the proposed data-driven framework, we first cast our proposed conditions of M-CBC as a robust optimization program (ROP). Given that the unknown model appears in some of the constraints of the ROP, we propose a sampling approach for collecting data and provide a scenario optimization program (SOP) associated with the proposed ROP. We solve the resulted SOP and construct M-CBC together with safety controllers for the unknown system with 100% correctness guarantee. We apply our results to a nonlinear jet engine compressor with unknown dynamics to illustrate the efficacy of our data-driven approach. In the case study, we show that while there exists no common polynomial-type control barrier certificate of a given degree, there exist polynomial-type M-CBC of the same degree by partitioning the state set to different regions.
|
|
13:50-14:10, Paper FrB02.2 | |
>Reachability Analysis of ARMAX Models (I) |
|
Lützow, Laura | Technical University Munich |
Althoff, Matthias | Technische Universität München |
Keywords: Formal Verification/Synthesis, Identification, Uncertain systems
Abstract: Reachability analysis is a powerful tool for computing the set of states or outputs reachable for a system. While previous work has focused on systems described by state-space models, we present the first methods to compute reachable sets of ARMAX models - one of the most common input-output models originating from data-driven system identification. The first approach we propose can only be used with dependency-preserving set representations such as symbolic zonotopes, while the second one is valid for arbitrary set representations but relies on a reformulation of the ARMAX model. By analyzing the computational complexities, we show that both approaches scale quadratically with respect to the time horizon of the reachability problem when using symbolic zonotopes. To reduce the computational complexity, we propose a third approach that scales linearly with respect to the time horizon when using set representations that are closed under Minkowski addition and linear transformation and that satisfy that the computational complexity of the Minkowski sum is independent of the representation size of the operands. Our numerical experiments demonstrate that the reachable sets of ARMAX models are tighter than the reachable sets of equivalent state space models in case of unknown initial states. Therefore, this methodology has the potential to significantly reduce the conservatism of various verification techniques.
|
|
14:10-14:30, Paper FrB02.3 | |
>Verifying the Unknown: Correct-By-Design Control Synthesis for Networks of Stochastic Uncertain Systems (I) |
|
Schön, Oliver | Newcastle University |
van Huijgevoort, Birgit | Eindhoven University of Technology |
Haesaert, Sofie | Eindhoven University of Technology |
Soudjani, Sadegh | Newcastle University |
Keywords: Formal Verification/Synthesis, Uncertain systems, Large-scale systems
Abstract: In this paper, we present an approach for designing correct-by-design controllers for cyber-physical systems composed of multiple dynamically interconnected uncertain systems. We consider networked discrete-time uncertain nonlinear systems with additive stochastic noise and model parametric uncertainty. Such settings arise when multiple systems interact in an uncertain environment and only observational data is available. We address two limitations of existing approaches for formal synthesis of controllers for networks of uncertain systems satisfying complex temporal specifications. Firstly, whilst existing approaches rely on the stochasticity to be Gaussian, the heterogeneous nature of composed systems typically yields a more complex stochastic behavior. Secondly, exact models of the systems involved are generally not available or difficult to acquire. To address these challenges, we show how abstraction-based control synthesis for uncertain systems based on sub-probability couplings can be extended to networked systems. We design controllers based on parameter uncertainty sets identified from observational data and approximate possibly arbitrary noise distributions using Gaussian mixture models whilst quantifying the incurred stochastic coupling. Finally, we demonstrate the effectiveness of our approach on a nonlinear package delivery case study with a complex specification, and a platoon of cars.
|
|
14:30-14:50, Paper FrB02.4 | |
>Data-Driven Reachability Analysis of Lipschitz Nonlinear Systems Via Support Vector Data Description (I) |
|
Wang, Zheming | Zhejiang University of Technology |
Chen, Bo | Zhejiang University of Technology |
Jungers, Raphaël M. | University of Louvain |
Yu, Li | Zhejiang University of Technology |
Keywords: Formal Verification/Synthesis, Learning, Randomized algorithms
Abstract: This paper is concerned with data-driven reachability analysis of discrete-time nonlinear systems without any dynamical model. We use only a number of observations of trajectories of the system to estimate the actual reachable set. With the data set, using the Support Vector Data Description (SVDD) technique, we propose a sample-based approximation method to solve the reachability analysis problem, which can be considered as a one-class classification problem. Under the framework of scenario optimization, we then derive over-approximations of the reachable set in a probabilistic sense with Lipschitz continuity and other regularity conditions. Finally, we demonstrate the proposed method on a numerical example.
|
|
14:50-15:10, Paper FrB02.5 | |
>Learning Robust and Correct Controllers from Signal Temporal Logic Specifications Using BarrierNet (I) |
|
Liu, Wenliang | Boston University |
Xiao, Wei | Massachusetts Institute of Technology |
Belta, Calin | Boston University |
Keywords: Formal Verification/Synthesis, Neural networks, Optimal control
Abstract: We consider the problem of learning a neural network controller for a system required to satisfy a Signal Temporal Logic (STL) specification. We exploit STL quantitative semantics to define a notion of robust satisfaction. Guaranteeing the correctness of a neural network controller is a difficult problem that received a lot of attention recently. We provide a general procedure to construct a set of trainable High Order Control Barrier Functions (HOCBFs) enforcing the satisfaction of formulas in a fragment of STL. We use the BarrierNet, implemented by a differentiable Quadratic Program (dQP) with HOCBF constraints, as the last layer of the neural network controller, to guarantee the satisfaction of the STL formulas. We train the HOCBFs together with other neural network parameters to further improve the robustness of the controller. Simulation results demonstrate that our approach ensures satisfaction and outperforms existing algorithms.
|
|
15:10-15:30, Paper FrB02.6 | |
>Stranding Risk for Underactuated Vessels in Complex Ocean Currents: Analysis and Controllers (I) |
|
Doering, Andreas | Technical University of Munich, University of California at Berk |
Wiggert, Marius | UC Berkeley |
Krasowski, Hanna | Technical University of Munich |
Doshi, Manan | Massachusetts Institute of Technology |
Lermusiaux, Pierre F. J. | Massachusetts Institute of Technology |
Tomlin, Claire J. | UC Berkeley |
Keywords: Maritime control, Autonomous robots, Predictive control for nonlinear systems
Abstract: Low-propulsion vessels can take advantage of powerful ocean currents to navigate towards a destination. Recent results demonstrated that vessels can reach their destination with high probability despite forecast errors. However, these results do not consider the critical aspect of safety of such vessels: because their propulsion is much smaller than the magnitude of surrounding currents, they might end up in currents that inevitably push them into unsafe areas such as shallow waters, garbage patches, and shipping lanes. In this work, we first investigate the risk of stranding for passively floating vessels in the Northeast Pacific. We find that at least 5.04% would strand within 90 days. Next, we encode the unsafe sets as hard constraints into Hamilton-Jacobi Multi-Time Reachability to synthesize a feedback policy that is equivalent to re-planning at each time step at low computational cost. While applying this policy guarantees safe operation when the currents are known, in realistic situations only imperfect forecasts are available. Hence, we demonstrate the safety of our approach empirically with large-scale realistic simulations of a vessel navigating in high-risk regions in the Northeast Pacific. We find that applying our policy closed-loop with daily re-planning as new forecasts become available reduces stranding below 1% despite forecast errors often exceeding the maximal propulsion. Our method significantly improves safety over the baselines and still achieves a timely arrival of the vessel at the destination.
|
|
FrB03 |
Orchid Main 4204-4305 |
Cyber-Physical Systems: Safety, Security, and Reliability |
Invited Session |
Chair: Sadabadi, Mahdieh S. | Queen Mary University of London |
Co-Chair: Escudero, Cédric | INSA Lyon, Laboratoire Ampère |
Organizer: Sadabadi, Mahdieh S. | University of Manchester |
Organizer: Escudero, Cédric | INSA Lyon, Laboratoire Ampère |
Organizer: Selvi, Daniela | Università Di Pisa |
Organizer: Soudjani, Sadegh | Newcastle University |
Organizer: Murguia, Carlos | Eindhoven University of Technology |
Organizer: Chong, Michelle | Eindhoven University of Technology |
Organizer: Ferrari, Riccardo M.G. | Delft University of Technology |
Organizer: Sasahara, Hampei | Tokyo Institute of Technology |
Organizer: Zhu, Quanyan | New York University |
|
13:30-13:50, Paper FrB03.1 | |
>Robust and Scalable Game-Theoretic Security Investment Methods for Voltage Stability of Power Systems (I) |
|
An, Lu | North Carolina State University |
Shukla, Pratishtha | Oak Ridge National Lab |
Chakrabortty, Aranya | North Carolina State University |
Duel-Hallen, Alexandra | North Carolina State University |
Keywords: Power systems, Game theory, Robust control
Abstract: We develop investment approaches to secure electric power systems against load attacks where a malicious intruder (the attacker) covertly changes reactive power setpoints of loads to push the grid towards voltage instability while the system operator (the defender) employs reactive power compensation (RPC) to prevent instability. Extending our previously reported Stackelberg game formulation for this problem, we develop a robust-defense sequential algorithm and a novel genetic algoirhtm that provides scalability to large-scale power system models. The proposed methods are validated using IEEE prototype power system models with time-varying load uncertainties, demonstrating that reliable and robust defense is feasible unless the operator's RPC investment resources are severely limited relative to the attacker's resources.
|
|
13:50-14:10, Paper FrB03.2 | |
>The Security Requirement to Prevent Zero Dynamics Attacks and Perfectly Undetectable Cyber-Attacks in Cyber-Physical Systems (I) |
|
Taheri, Mahdi | Concordia University |
Khorasani, Khashayar | Concordia University |
Meskin, Nader | Qatar University |
Keywords: Cyber-Physical Security
Abstract: The impacts of zero dynamics attacks and perfectly undetectable cyber-attacks cannot be observed in outputs of cyber-physical systems (CPS). Adversaries are capable of executing these cyber-attacks and leading the CPS to undesirable trajectories while remaining undetected. In this paper, we introduce and formally introduce the notion of security effort (SE) as a novel security metric for CPS that determines the minimum number of actuators and sensors that should be secured and kept attack free in order to prevent adversaries from executing zero dynamics attacks, covert attacks, and controllable attacks. Moreover, since zero dynamics attacks, covert attacks, and controllable attacks belong to weakly unobservable and controllable weakly unobservable subspaces of the CPS, conditions under which these subspaces become zero are obtained and investigated. An illustrative numerical simulation is provided to demonstrate the effectiveness of our proposed security measure.
|
|
14:10-14:30, Paper FrB03.3 | |
>Secure State Estimation with Asynchronous Measurements against Malicious Measurement-Data and Time-Stamp Manipulation (I) |
|
Li, Zishuo | Tsinghua University |
Nguyen, Anh Tung | Uppsala University |
Teixeira, André M. H. | Uppsala University |
Mo, Yilin | Tsinghua University |
Johansson, Karl H. | KTH Royal Institute of Technology |
Keywords: Sensor fusion, Fault tolerant systems, Cyber-Physical Security
Abstract: This paper proposes a secure state estimation scheme with asynchronous non-periodic measurements for continuous LTI systems under false data attacks on measurement transmission channels. Each sensor transmits the measurement information in a triple comprised of its sensor index, the time-stamp, and the measurement value to the fusion center via unprotected communication channels. A malicious attacker can corrupt a subset of sensors by (i) manipulating the time- stamp and the measurement value; (ii) blocking transmitted measurement triples; or (iii) injecting fake measurement triples. To deal with such attacks, we propose a secure state estimator by designing decentralized local estimators and fusing all the local states by the median operator. The local estimators receive the sampled measurements and update their local state in an asynchronous manner, while the fusion center triggers the fusion and generates a secure estimation in the presence of a local update. We prove that local estimators of benign sensors are unbiased with stable error covariance. Moreover, the fused secure estimation error has bounded expectation and covariance against at most p corrupted sensors as long as the system is 2p-sparse observable. The efficacy of the proposed scheme is demonstrated through a benchmark example of the IEEE 14-bus system.
|
|
14:30-14:50, Paper FrB03.4 | |
>Set-Based Anomaly Detector and Stealthy Attack Impact Using Constrained Zonotopes (I) |
|
Wagner, Jonas | University of Texas at Dallas |
Kogel, Tanner | University of Texas at Dallas |
Ruths, Justin | University of Texas at Dallas |
Keywords: Attack Detection, Cyber-Physical Security, Uncertain systems
Abstract: In this paper, a set-based detector is developed and analyzed based on the propagation of nominal (no attacks), actual (possibly with attacks), and perceived (corrupted by attacks) residuals due to bounded system and measurement noise uncertainties. The set of stealthy attacks (attacks that raise no alarms) is characterized and the impact of these stealthy attacks on the system state is quantified. When implemented through the set tools of constrained zonotopes, this approach provides accurate, time-varying attack-reachable sets that can be used to evaluate the safety and performance of systems in adversarial conditions. These tools are demonstrated through two case studies.
|
|
14:50-15:10, Paper FrB03.5 | |
>Electrical Fault Localisation Over a Distributed Parameter Transmission Line (I) |
|
Selvaratnam, Daniel | KTH Royal Institute of Technology |
Das, Amritam | Eindhoven University of Technology |
Sandberg, Henrik | KTH Royal Institute of Technology |
Keywords: Fault detection, Power systems, Estimation
Abstract: Motivated by the need to localise faults along electrical power lines, this paper adopts a frequency-domain approach to parameter estimation for an infinite-dimensional linear dynamical system with one spatial variable. Since the time of the fault is unknown, and voltages and currents are measured at only one end of the line, distance information must be extracted from the post-fault transients. To properly account for high-frequency transient behaviour, the line dynamics is modelled directly by the Telegrapher’s equation, rather than the more commonly used lumped-parameter approximations. First, the governing equations are non-dimensionalised to avoid ill-conditioning. A closed-form expression for the transfer function is then derived. Finally, nonlinear least-squares optimisation is employed to search for the fault location. Requirements on fault bandwidth, sensor bandwidth and simulation time-step are also presented. The result is a novel end-to-end algorithm for data generation and fault localisation, the effectiveness of which is demonstrated via simulation.
|
|
15:10-15:30, Paper FrB03.6 | |
>Adversarial Attacks to Direct Data-Driven Control for Destabilization (I) |
|
Sasahara, Hampei | Tokyo Institute of Technology |
Keywords: Cyber-Physical Security, Data driven control, Resilient Control Systems
Abstract: This study investigates the vulnerability of direct data-driven control to adversarial attacks in the form of a small but sophisticated perturbation added to the original data. The directed gradient sign method (DGSM) is developed as a specific attack method, based on the fast gradient sign method (FGSM), which has originally been considered in image classification. DGSM uses the gradient of the eigenvalues of the resulting closed-loop system and crafts a perturbation in the direction where the system becomes less stable. It is demonstrated that the system can be destabilized by the attack, even if the eigenvalues of the original closed-loop matrix with the clean data are aligned far from the unstable region. To increase the robustness against the attack, regularization methods that have been developed to deal with random disturbances are considered. Their effectiveness is evaluated by numerical experiments using an inverted pendulum model.
|
|
FrB04 |
Simpor Junior 4913 |
Autonomous Vehicles III |
Regular Session |
Chair: Malikopoulos, Andreas A. | University of Delaware |
Co-Chair: Oguri, Kenshiro | Purdue University |
|
13:30-13:50, Paper FrB04.1 | |
>NMPC Strategy for Safe Robot Navigation in Unknown Environments Using Polynomial Zonotopes |
|
Baptista Pereira Nascimento, Iuro | Federal University of Minas Gerais |
Rego, Brenner | Federal University of Minas Gerais |
Pimenta, Luciano C. A. | Universidade Federal De Minas Gerais |
Raffo, Guilherme Vianna | Federal University of Minas Gerais |
Keywords: Autonomous vehicles, Predictive control for nonlinear systems, Robotics
Abstract: This work proposes a nonlinear model predictive control (NMPC) strategy for robot navigation in cluttered unknown environments using polynomial zonotopes. The infor- mation provided by a laser sensor is used in the computation of the collision-free area. The procedure splits the area into convex subregions which are converted into polynomial zonotopes (PZs) to generate constraints for the NMPC optimal control problem. The PZ is a set representation that can describe polytopes using fewer constraints than conventional half-space representations, thus being more efficient while maintaining the accuracy equiv- alent to the polytopic case. Numerical experiments demonstrate the advantages of the proposed strategy.
|
|
13:50-14:10, Paper FrB04.2 | |
>A Hierarchical Approach to Optimal Flow-Based Routing and Coordination of Connected and Automated Vehicles |
|
Bang, Heeseung | University of Delaware |
Malikopoulos, Andreas A. | Cornell University |
Keywords: Autonomous vehicles, Traffic control, Transportation networks
Abstract: This paper addresses the challenge of generating optimal vehicle flow at the macroscopic level. Although several studies have focused on optimizing vehicle flow, little attention has been given to ensuring it can be practically achieved. To overcome this issue, we propose a route-recovery and eco-driving strategy for connected and automated vehicles (CAVs) that guarantees optimal flow generation. Our approach involves identifying the optimal vehicle flow that minimizes total travel time, given the constant travel demands in urban areas. We then develop a heuristic route-recovery algorithm to assign routes to CAVs. Finally, we present an efficient coordination framework to minimize the energy consumption of CAVs while safely crossing intersections. The proposed method can effectively generate optimal vehicle flow and potentially reduce travel time and energy consumption in urban areas.
|
|
14:10-14:30, Paper FrB04.3 | |
>Multi-Occlusions Inference from Multiple Social Vehicles |
|
Zhao, Xuhe | Tongji University |
Zhang, Chaojie | Tongji University |
Wang, Jun | Tongji University |
Keywords: Autonomous vehicles
Abstract: Occlusions at intersections threaten the safety of autonomous driving, especially in urban scenarios. Phantom vehicles are usually considered to mitigate the risks associated with the occlusions, and their states may be inferred from observable vehicles. This paper extends these methods to deal with multiple occlusions and multiple inferences. A multi-occlusion aware model allows for the concerns of occluded areas and the configuration of phantom vehicles. The evidence theory fuses multiple estimations to enhance occlusion inferences. Simulations for intersection scenarios are conducted to demonstrate the effectiveness of the proposed method for improving traffic efficiency.
|
|
14:30-14:50, Paper FrB04.4 | |
>Robust Collision Avoidance of Quadric and Polygonal Surfaces Moving in Planar Environments |
|
Dhal, Kashish | The University of Texas at Arlington |
Kashyap, Abhishek | University of Texas at Arlington |
Chakravarthy, Animesh | University of Texas at Arlington |
Keywords: Autonomous vehicles
Abstract: The determination of robot trajectories that can achieve reactive collision avoidance with moving objects is of great interest. In cluttered environments with tight spaces, it becomes important to consider the shapes of the objects in computing these trajectories. The literature largely models the shapes of the objects as circles, and this can make the avoidance maneuvers very conservative, especially when the objects are elongated and/or non-convex. In this paper, we model the shapes of the objects using combinations of quadric surfaces or polygons, and employ a collision cone approach to achieve reactive collision avoidance, in the presence of measurement noise. The collision avoidance design employs a dual-loop control architecture where the inner loop uses a dynamic inversion-based method and the outer loop uses Linear Matrix Inequalities (LMIs). Simulation results demonstrating the the collision avoidance laws for dynamic, heterogeneous quadric and polygonal surfaces are presented.
|
|
14:50-15:10, Paper FrB04.5 | |
>Capturability of the Pulsed Guidance Law Based on Differential Game Theory |
|
Lu, Yuting | Beihang University |
Yu, Yang | Beihang University |
Zhao, Qilun | Beijing Institute of Electronic System Engineering |
Han, Tuo | Beihang University |
Hu, Qinglei | Beihang University |
Li, Dongyu | Beihang University |
Keywords: Autonomous vehicles
Abstract: The capturability analysis of the pulsed guidance law using differential game theory is presented in this paper. The engagement of an interceptor with pulsed guidance constraint and a maneuvering target with bounded acceleration is considered. The differential game guidance laws for both the interceptor and the target are proposed. Then the engagement is converted into four different cases according to the guidance law parameters, and the capture boundary conditions for these four cases are given as functions of the guidance law parameters and the system parameters, including acceleration constraints, the acceptable miss distance and initial values of the engagement. Afterwards, the capture zone is given according to the boundary conditions and is decided by the guidance law parameters and the system parameters. Finally, various specific examples show that the interception can be guaranteed with lower acceleration constraint ratio and higher guidance law parameter ratio.
|
|
15:10-15:30, Paper FrB04.6 | |
>Smooth Indirect Solution Method for State-Constrained Optimal Control Problems with Nonlinear Control-Affine Systems |
|
Oguri, Kenshiro | Purdue University |
Keywords: Aerospace, Optimal control, Autonomous vehicles
Abstract: This paper presents an indirect solution method for state-constrained optimal control problems to address the long-standing issue of discontinuous control and costate under state constraints. It is known in optimal control theory that a state inequality constraint introduces discontinuities in control and costate, rendering the classical indirect solution methods ineffective. This study re-examines the necessary conditions of optimality for a class of state-constrained optimal control problems, and shows the uniqueness of the optimal control that minimizes the Hamiltonian under state constraints, which leads to a unifying form of the necessary conditions. The unified form of the necessary conditions opens the door to addressing the issue of discontinuities in control and costate by modeling them via smooth functions. This paper exploits this insight to transform the originally discontinuous problems to smooth two-point boundary value problems that can be solved by existing nonlinear root-finding algorithms. This paper also shows the formulated solution method to have an anytime algorithm-like property, and then numerically demonstrates the solution method by an optimal orbit control problem.
|
|
FrB05 |
Simpor Junior 4912 |
Learning and Decision-Making in Multi-Agent Systems |
Invited Session |
Chair: Anderson, James | Columbia University |
Co-Chair: Mitra, Aritra | University of Pennsylvania |
Organizer: Anderson, James | Columbia University |
Organizer: Mitra, Aritra | University of Pennsylvania |
Organizer: Pappas, George J. | University of Pennsylvania |
|
13:30-13:50, Paper FrB05.1 | |
>Multi-Agent Reinforcement Learning for Resource Allocation in Large-Scale Robotic Warehouse Sortation Centers (I) |
|
Shen, Yi | Duke University |
McClosky, Benjamin | Amazon Robotics |
Durham, Joseph W. | Kiva Systems |
Zavlanos, Michael M. | Duke University |
Keywords: Agents-based systems, Building and facility automation, Learning
Abstract: Robotic sortation centers use mobile robots to sort packages by their destinations. The destination-to-sort- location (chute) mapping can significantly impact the volume of packages that can be sorted by the sortation floor. In this work, we propose a multi-agent reinforcement learning method to solve large-scale chute mapping problems with hundreds of agents (the destinations). To address the exponential growth of the state-action space, we decompose the joint action-value function as the sum of local action-value functions associated with the individual agents. To incorporate robot congestion effects on the rates at which packages are sorted, we couple the local action-value functions through the states of destinations mapped to nearby chutes on the sortation floor. We show that our proposed framework can solve large chute mapping problems and outperforms static or reactive policies that are commonly used in practice in robotic sortation facilities.
|
|
13:50-14:10, Paper FrB05.2 | |
>Performance Bounds for Policy-Based Reinforcement Learning Methods in Zero-Sum Markov Games with Linear Function Approximation (I) |
|
Winnicki, Anna | University of Illinois at Urbana Champaign |
Srikant, R | Univ of Illinois, Urbana-Champaign |
Keywords: Stochastic optimal control, Game theory
Abstract: Until recently, efficient policy iteration algorithms for zero-sum Markov games that converge were unknown. Therefore, model-based RL algorithms for such problems could not use policy iteration in the planning modules of the algorithms. In an earlier paper, we showed that a convergent policy iteration algorithm can be obtained by using a commonly used technique in RL called lookahead. However, the algorithm could be applied to the function approximation setting only in the special case of linear MDPs (Markov Decision Processes). In this paper, we obtain performance bounds for policy-based RL algorithms for general settings, including one where policy evaluation is performed using noisy samples of (state, action, reward) triplets from a single sample path of a given policy.
|
|
14:10-14:30, Paper FrB05.3 | |
>Motion Planning for the Estimation of Functions (I) |
|
Raghavan, Aneesh | KTH Royal Insitute of Technology |
Sartori, Giacomo | UNIPD |
Johansson, Karl H. | KTH Royal Institute of Technology |
Keywords: Learning, Optimization, Numerical algorithms
Abstract: We consider the problem of estimation of an unknown real valued function with real valued input by an agent. The agent exists in 3D Euclidean space. It is able to traverse in a 2D plane while the function is depicted in a 2D plane perpendicular to the plane of traversal. By viewing the function from a given position, the agent is able to collect a data point lying on the function. By traversing through the plane while paying a control cost, the agent collects a finite set of data points. The set of data points are used by the agent to estimate the function. The objective of the agent is to find a control law which minimizes the control cost while estimating the function optimally. We formulate a control problem for the agent incorporating an inference cost and the control cost. The control problem is relaxed by finding a lower bound for the cost function. We present a kernel based linear regression model to approximate the cost-to-go and use the same in a control algorithm to solve the relaxed optimization problem. We present simulation results comparing the proposed approach with greedy algorithm based exploration.
|
|
14:30-14:50, Paper FrB05.4 | |
>Learning Agent Interactions from Density Evolution in 3D Regions with Obstacles (I) |
|
Tirumalai, Amoolya | University of Maryland, Institute for Systems Research |
Mavridis, Christos | University of Maryland, College Park |
Baras, John S. | University of Maryland |
Keywords: Identification, Agents-based systems, Computational methods
Abstract: In this work, we study the inverse problem of identifying complex flocking dynamics in a domain cluttered with obstacles. We get inspiration from animal flocks moving in complex ways with capabilities far beyond what current robots can do. Owing to the difficulty of observing and recovering the trajectories of the agents, we focus on the dynamics of their probability densities, which are governed by partial differential equations (PDEs), namely compressible Euler equations subject to non-local forces. We formulate the inverse problem of learning interactions as a PDE-constrained optimization problem of minimizing the squared Hellinger distance between the histogram of the flock and the distribution associated to our PDEs. The numerical methods used to efficiently solve the PDE-constrained optimization problem are described. Realistic flocking data are simulated using the Boids model of flocking agents, which differs in nature from the reconstruction models used in our PDEs. Our analysis and simulated experiments show that the behavior of cohesive flocks can be recovered accurately with approximate PDE solutions.
|
|
14:50-15:10, Paper FrB05.5 | |
>Learning Personalized Models with Clustered System Identification (I) |
|
Toso, Leonardo Felipe | Columbia University |
Wang, Han | Columbia University |
Anderson, James | Columbia University |
Keywords: Statistical learning, Linear systems, Optimization
Abstract: We address the problem of learning linear system models by observing multiple trajectories from systems with differing dynamics. This framework encompasses a collaborative scenario where several systems seeking to estimate their dynamics are partitioned into clusters according to system similarity. Thus, the systems within the same cluster can benefit from the observations made by the others. Considering this framework, we present an algorithm where each system alternately estimates its cluster identity and performs an estimation of its dynamics. This is then aggregated to update the model of each cluster. We show that under mild assumptions, our algorithm correctly estimates the cluster identities and achieves an epsilon-approximate solution with a sample complexity that scales inversely with the number of systems in the cluster, thus facilitating a more efficient and personalized system identification.
|
|
15:10-15:30, Paper FrB05.6 | |
>Decentralized Conflict Resolution for Multi-Agent Reinforcement Learning through Shared Scheduling Protocol (I) |
|
Ingebrand, Tyler | UT Austin |
Smith, Sophia | The University of Texas at Austin |
Topcu, Ufuk | The University of Texas at Austin |
Keywords: Decentralized control, Learning, Cooperative control
Abstract: Decentralized multi-agent reinforcement learning (MARL) is an inherently difficult problem because agents can have individual, unique objectives and no direct incentive to cooperate. Conflicts often arise over bottlenecks in the environment, such as a shared key or an intersection, where multiple agents need to access a single resource. To resolve these conflicts, we propose the use of a shared scheduling protocol. A scheduling protocol coordinates agent behavior such that one agent is allowed to greedily use the resource while the others are required to wait. In particular, we are interested in decentralized scheduling protocols that can be implemented independently by each agent without a centralized controller. We present three protocols and prove that they resolve conflicts when obeyed by all agents. In training, agents learn to obey the protocol as violations incur a penalty. Experimental results show that scheduling protocols increase the performance of multi-agent training fivefold compared to baseline decentralized MARL.
|
|
FrB06 |
Simpor Junior 4911 |
Estimation and Control of Quantum Systems |
Invited Session |
Chair: Dong, Daoyi | University of New South Wales |
Co-Chair: Amini, Nina H. | CNRS, L2S, CentraleSupelec |
Organizer: Dong, Daoyi | Australian National University |
Organizer: Amini, Nina H. | CNRS, L2S, CentraleSupelec |
Organizer: Wang, Yuanlong | Chinese Academy of Sciences |
|
13:30-13:50, Paper FrB06.1 | |
>Two-Stage Solution for Ancilla-Assisted Quantum Process Tomography: Error Analysis and Optimal Design (I) |
|
Xiao, Shuixin | Shanghai Jiao Tong University |
Wang, Yuanlong | Chinese Academy of Sciences |
Dong, Daoyi | University of New South Wales |
Zhang, Jun | Shanghai Jiao Tong University |
Keywords: Quantum information and control
Abstract: Quantum process tomography (QPT) is a fundamental task to characterize the dynamics of quantum systems. In contrast to standard QPT, ancilla-assisted process tomography (AAPT) framework introduces an extra ancilla system such that a single input state is needed. In this paper, we extend the two-stage solution, a method originally designed for standard QPT, to perform AAPT. Our algorithm has O(Md_A^2d_B^2) computational complexity where M is the type number of the measurement operators, d_A is the dimension of the quantum system of interest, and d_B is the dimension of the ancilla system. Then we establish an error upper bound and further discuss the optimal design on the input state in AAPT. A numerical example on a phase damping process demonstrates the effectiveness of the optimal design and illustrates the theoretical error analysis.
|
|
13:50-14:10, Paper FrB06.2 | |
>Analyzing and Unifying Robustness Measures for Excitation Transfer Control in Spin Networks |
|
O'Neil, Sean Patrick | University of Southern California |
Khalid, Irtaza | Cardiff University |
Rompokos, Athanasios | University of Southern California |
Weidner, Carrie Ann | University of Bristol |
Langbein, Frank C. | Cardiff University |
Schirmer, Sophie | Swansea University |
Jonckheere, Edmond | University of Southern California |
Keywords: Robust control, Quantum information and control
Abstract: Recent achievements in quantum control have resulted in advanced techniques for designing controllers for applications in quantum communication, computing, and sensing. However, the susceptibility of such systems to noise and uncertainties necessitates robust controllers that perform effectively under these conditions to realize the full potential of quantum devices. The time-domain log-sensitivity and a recently introduced robustness infidelity measure (RIM) are two means to quantify controller robustness in quantum systems. The former can be found analytically, while the latter requires Monte-Carlo sampling. In this work, the correlation between the log-sensitivity and the RIM for evaluating the robustness of single excitation transfer fidelity in spin chains and rings in the presence of dephasing is investigated. We show that the expected differential sensitivity of the error agrees with the differential sensitivity of the RIM, where the expectation is over the error probability distribution. Statistical analysis also demonstrates that the log-sensitivity and the RIM are linked via the differential sensitivity, and that the differential sensitivity and RIM are highly concordant. This unification of two means (one analytic and one via sampling) to assess controller robustness in a variety of realistic scenarios provides a first step in unifying various tools to model and assess robustness of quantum controllers.
|
|
14:10-14:30, Paper FrB06.3 | |
>On the Mean-Field Belavkin Filtering Equation |
|
Chalal, Sofiane | CentraleSupelec/Université Paris-Saclay |
Amini, Nina H. | CNRS, L2S, CentraleSupelec |
Guo, Gaoyue | MICS/CentraleSupelec |
Keywords: Quantum information and control, Stochastic systems, Mean field games
Abstract: Following Kolokoltsov’s work [1], we present an extension of mean-field control theory in quantum framework. In particular such an extension is done naturally by considering the Belavkin quantum filtering and control theory in a mean- field setting. In this setting, the dynamics is described by a controlled Belavkin equation of McKean-Vlasov type. We prove the well-posedness of such an equation under imperfect measurement records. Furthermore, we show under purification assumption the propagation of chaos for perfect measurements. Finally, we apply particle methods to simulate the mean- field Belavkin equation and we provide numerical simulations showing the stabilization of the mean-field Belavkin equation by a feedback control strategy towards a chosen target state.
|
|
14:30-14:50, Paper FrB06.4 | |
>Quantum Optimal Control for the Shaping of Single Photons (I) |
|
Dong, Xue | Tsinghua University |
Wu, Re-Bing | Tsinghua University |
Keywords: Quantum information and control, Optimal control
Abstract: The transmission of flying qubits carried by itinerant photons is fundamental in quantum communication networks. To physically match the receiver system, the single photons must be prepared in proper shapes, and this leads to a variety of flying-qubit control problems. In this paper, we introduce the optimal control theory to the shaping of single photons, where the control to be optimized are coherent driving fields. We design gradient-based algorithms to minimize the shape difference between the emitted and desired single photons. Simulation results show that the optimization can achieve high-fidelity in the generation of decaying photon shapes with a two-level atom. However, its performance is limited and hence has to be combined with incoherence controls when the target shape has a rising part.
|
|
14:50-15:10, Paper FrB06.5 | |
>On the Robustness of Stability for Quantum Stochastic Systems (I) |
|
Liang, Weichao | CentraleSupelec, University of Paris Saclay |
Ohki, Kentaro | Kyoto University |
Ticozzi, Francesco | Università Di Padova |
Keywords: Quantum information and control, Robust control, Lyapunov methods
Abstract: We investigate the impact of undesired Markovian couplings to external systems on the stabilization towards pure states or subspaces of continuously monitored quantum systems under open-loop and feedback control protocols. In particular, we provide sufficient conditions on perturbations to maintain stability of the target and demonstrate the boundedness in mean of the solutions of perturbed systems under open-loop protocols. Effect on the stability of feedback protocols is also analyzed. This work is a step toward a comprehensive robustness analysis of measurement-based control of quantum systems with respect to model perturbations.
|
|
15:10-15:30, Paper FrB06.6 | |
>Heisenberg Formulation of Adiabatic Elimination for Open Quantum Systems with Two TimeScales (I) |
|
Le Régent, Francçois-Marie | Alice&Bob |
Rouchon, Pierre | Mines Paris PSL |
Keywords: Quantum information and control, Reduced order modeling
Abstract: Consider an open quantum system governed by a Gorini–Kossakowski–Sudarshan–Lindblad master equation with two times-scales: a fast one, exponentially converging towards a linear subspace of quasi-equilibria; a slow one resulting from small decoherence and Hamiltonian dynamics. Usually adiabatic elimination is performed in the Schrödinger picture. We propose here a Heisenberg formulation where the invariant operators attached to the fast decay dynamics towards the quasi-equilibria subspace play a key role. Based on geometric singular perturbations, asymptotic expansions of the Heisenberg slow dynamics and of the fast invariant linear subspaces are proposed. They exploit Carr's approximation lemma from center-manifold and bifurcation theory. Second-order expansions are detailed and shown to ensure preservation, up to second-order terms, of the complete positivity for the slow propagator on a slow timescale. Such expansions can be exploited numerically to derive reduced-order dynamical models.
|
|
FrB07 |
Simpor Junior 4813 |
Game Theory VI |
Regular Session |
Chair: Wang, Bing-Chang | Shandong University |
Co-Chair: Fu, Jie | University of Florida |
|
13:30-13:50, Paper FrB07.1 | |
>Open-Loop Saddle Points for Irregular Linear-Quadratic Two-Person Zero-Sum Games (I) |
|
Liang, Yong | Shandong University |
Wang, Bing-Chang | Shandong University |
Xu, Juanjuan | Shandong University |
Zhang, Huanshui | Shandong University of Science and Technology |
Keywords: Linear systems, Optimal control, Game theory
Abstract: In this paper, we consider the feedback representation of open-loop saddle points for irregular linear-quadratic (LQ) two-person zero-sum games, where the control weighting matrices in the cost functional are only semidefinite. The existence of an open-loop saddle point is characterized by the solvability of a system of constrained linear forward-backward differential equations (FBDEs), together with a convexity-concavity condition. In classical zero-sum games, the feedback representation is obtained by decoupling the FBDEs through the regular solution to a Riccati differential equation. But the associated Riccati equation cannot be used to decouple the FBDEs to obtain the feedback representation of open-loop saddle points. The essential differences between regular and irregular LQ zero-sum games are investigated. The irregular feedback representation can be derived from two equilibrium conditions in two different layers by using the ``two-layer optimization" approach.
|
|
13:50-14:10, Paper FrB07.2 | |
>Linear Convergence in Time-Varying Generalized Nash Equilibrium Problems |
|
Bianchi, Mattia | ETH Zurich |
Benenati, Emilio | Technische Universiteit Delft |
Grammatico, Sergio | Delft Univ. of Tech |
Keywords: Optimization algorithms, Game theory, Variational methods
Abstract: We study generalized games with full row rank equality constraints and we provide a strikingly simple proof of strong monotonicity of the associated KKT operator. This allows us to show linear convergence to a variational equilibrium of the resulting primal-dual pseudo-gradient dynamics. Next, we propose a fully-distributed algorithm with linear convergence guarantee for aggregative games under partial-decision information. Based on these results, we establish stability properties for online GNE seeking in games with time-varying cost functions and constraints. Finally, we illustrate our findings numerically on an economic dispatch problem for peer-to-peer energy markets.
|
|
14:10-14:30, Paper FrB07.3 | |
>Multi-Agent Reach-Avoid Games: Two Attackers versus One Defender and Mixed Integer Programming |
|
Hu, Hanyang | Simon Fraser University |
Bui, Nhat Minh | Simon Fraser University |
Chen, Mo | Simon Fraser University |
Keywords: Optimal control, Game theory, Intelligent systems
Abstract: We propose a hybrid approach that combines Hamilton-Jacobi (HJ) reachability and mixed-integer optimiza- tion for solving a reach-avoid game with multiple attackers and defenders. The reach-avoid game is an important problem with potential applications in air traffic control and multi- agent motion planning; however, solving this game for many attackers and defenders is intractable due to the adversarial nature of the agents and the high problem dimensionality. In this paper, we first propose an HJ reachability-based method for solving the reach-avoid game in which 2 attackers are playing against 1 defender; we derive the numerically convergent optimal winning sets for the two sides in environments with obstacles. Utilizing this result and previous results for the 1 vs. 1 game, we further propose solving the general multi-agent reach-avoid game by determining the defender assignments that can maximize the number of attackers captured via a Mixed Integer Program (MIP). Our method generalizes previous state- of-the-art results and is especially useful when there are fewer defenders than attackers. We validate our theoretical results in numerical simulations.
|
|
14:30-14:50, Paper FrB07.4 | |
>Games for Efficient Supervisor Synthesis |
|
Jha, Prabhat Kumar | Chalmers University of Technology |
Hausmann, Daniel | Gothenburg University |
Piterman, Nir | University of Gothenburg |
Keywords: Supervisory control, Game theory, Discrete event systems
Abstract: In recent years, there was an increasing interest in the connections between supervisory control theory and reactive synthesis. As the two fields use similar techniques there is great hope that technologies from one field could be used in the other. In this spirit, we provide an alternative reduction from the supervisor synthesis problem to solving B"uchi games via games with a non-blocking objective. Our reduction is more compact and uniform than previous reductions. As a consequence, it gives an asymptotically better upper bound on the time complexity of the supervisory control synthesis problem. Our reduction also breaks a widely held belief about the impossibility of reduction of supervisory control synthesis problem to a game with linear winning condition.
|
|
14:50-15:10, Paper FrB07.5 | |
>Synthesis of Opacity-Enforcing Winning Strategies against Colluded Opponent |
|
Shi, Chongyang | University of Florida |
Kulkarni, Abhishek | University of Florida at Gainesville |
Rahmani, Hazhar | University of Florida |
Fu, Jie | University of Florida |
Keywords: Discrete event systems, Formal Verification/Synthesis, Game theory
Abstract: This paper studies language-based opacity enforcement in a two-player, zero-sum game on a graph. In this game, player 1 (P1) wins if he can achieve a secret temporal goal described by the language of a finite automaton, no matter what strategy the opponent player 2 (P2) selects. In addition, P1 aims to win while making its goal opaque to a passive observer with imperfect information. However, P2 colludes with the observer to reveal P1's secret whenever P2 cannot prevent P1 from achieving its goal, and therefore, opacity must be enforced against P2. We show that a winning and opacity-enforcing strategy for P1 can be computed by reducing the problem to solving a reachability game augmented with the observer's belief states. Furthermore, if such a strategy does not exist, winning for P1 must entail the price of revealing his secret to the observer. We demonstrate our game-theoretic solution of opacity-enforcement control through a small illustrative example and in a robot motion planning problem.
|
|
15:10-15:30, Paper FrB07.6 | |
>A Stackelberg Viral Marketing Design for Two Competing Players |
|
Lindamulage de silva, Olivier | Université De Lorraine, CRAN |
Satheeskumar Varma, Vineeth | CNRS |
Cao, Ming | University of Groningen |
Morarescu, Irinel-Constantin | CRAN, CNRS, Université De Lorraine |
Lasaulce, Samson | CNRS |
Keywords: Game theory
Abstract: A Stackelberg duopoly model in which two firms compete to maximize their market share is considered. The firms offer a service/product to customers that are spread over several geographical regions (e.g., countries, provinces, or states). We use a bi-virus Susceptible-Infected-Susceptible (SIS) model to characterize the spreading of the service/product offered by the two firms. Each region has its own characteristics (spreading and recovery rates) of each service propagation. We consider that the spreading rate can be controlled by each firm and is subject to some investment that the firm does in each region. One of the main objectives of this work is to characterize the advertising budget allocation strategy for each firm across regions to maximize its market share when competing. To achieve this goal we propose a Stackelberg game model that is relatively simple while capturing the main effects of the competition for market share. By characterizing the equilibria of the two-level Stackelberg game in the pessimistic/optimistic settings we provide the associated budget allocation strategy. In this setting, it is established under which conditions the solution of the game is the so-called ”winner takes all”. Numerical results expand upon our theoretical findings and we provide the equilibrium characterization for an example.
|
|
FrB08 |
Simpor Junior 4812 |
Optimization Algorithms VI |
Regular Session |
Chair: Daoutidis, Prodromos | Univ. of Minnesota |
Co-Chair: Ahn, Hyo-Sung | Gwangju Institute of Science and Technology (GIST) |
|
13:30-13:50, Paper FrB08.1 | |
>Preconditioning Matrix Synthesis for a Projected Gradient Method for Solving Constrained Linear-Quadratic Optimal Control Problems |
|
Heuts, Yannick (Y.J.J.) | Eindhoven University of Technology |
Donkers, M.C.F. | Eindhoven University of Technology |
Keywords: Numerical algorithms, LMIs, Optimization algorithms
Abstract: This paper presents a method for synthesizing preconditioning matrices for a heavy-ball accelerated projected primal-dual method. The main focus lies on linear quadratic optimal control problems, as they have a specific structure that can be exploited for fast computational times. This gradient method is rewritten into a Lur'e-type system, such that convergence of the algorithm can be enforced through finding an appropriate Lyapunov function for the Lur'e system. It has been shown that for a small problem, it is possible to synthesize preconditioning matrices and that the method is 10^4 times faster than solving the projection using a dedicated solver.
|
|
13:50-14:10, Paper FrB08.2 | |
>Distributed Least Square Approach for Solving a Multiagent Linear Algebraic Equation |
|
Pham, Viet Hoang | GIST |
Ahn, Hyo-Sung | Gwangju Institute of Science and Technology (GIST) |
Keywords: Agents-based systems, Optimization algorithms, Linear systems
Abstract: This paper considers a linear algebraic equation over a multiagent network. The coefficient matrix is partitioned into multiple blocks; each agent only knows a subset of these blocks in different row and column partitions. Based on a proximal ADMM algorithm, we design a distributed method for every agent to find its corresponding parts in one least square solution of the considered linear algebraic equation. Each agent uses only its information and communicates with its neighbors. We show that the designed method achieves an exponentially fast convergence for an arbitrary initial setup. Numerical simulations in MATLAB are provided to verify the effectiveness of the designed method.
|
|
14:10-14:30, Paper FrB08.3 | |
>On Receding-Horizon Approximation in Time-Varying Optimal Control |
|
Sun, Jintao | University of Melbourne |
Cantoni, Michael | University of Melbourne |
Keywords: Time-varying systems, Predictive control for linear systems, Optimal control
Abstract: The closed-loop stability and infinite-horizon performance of receding-horizon approximations are studied for non-stationary linear-quadratic regulator (LQR) problems. The approach is based on a lifted reformulation of the optimal control problem, under assumed uniform controllability and observability, leading to a strict contraction property of the corresponding Riccati operator. Leveraging this contraction property, a stabilizing linear time-varying state-feedback approximation of the infinite-horizon optimal control policy is constructed to meet a performance-loss specification. Its synthesis involves only finite preview of the time-varying problem data at each time step, over a sufficiently long prediction horizon.
|
|
14:30-14:50, Paper FrB08.4 | |
>Exact Noise-Robust Distributed Gradient-Tracking Algorithm for Constraint-Coupled Resource Allocation Problems (I) |
|
Wu, Wenwen | Shanghai Jiao Tong University |
Zhu, Shanying | Shanghai Jiao Tong University |
Liu, Shuai | Shandong University |
Guan, Xin-Ping | Shanghai Jiao Tong University |
Keywords: Optimization algorithms, Distributed control, Agents-based systems
Abstract: The Industrial Internet of Things gradually becomes a new paradigm for information exchange in the industrial production environment. To ensure the high reliability of IIoT services, an efficient resource allocation method with good robustness is urgently needed under complex industrial environments. This paper considers the distributed constraint-coupled resource allocation problem with noisy information exchange over an undirected network, where each agent holds a private cost function and obtains the solution via only local communications. Communication noise poses a challenge to gradient-tracking based algorithm as the impact of noise will accumulate and its variance tends to infinity when the noise is persistent. Adopting noise-tracing scheme, we propose an exact noise-robust distributed gradient-tracking algorithm to achieve cost-optimal distribution of resources, which can avoid noise-accumulation in the tracking step. Moreover, noise suppression parameters are introduced to further attenuate the impact of noise. With diminishing suppression parameters, it is theoretically proved that the proposed algorithm is able to achieve exact convergence to the optimal solution. Finally, a numerical example is provided for verification.
|
|
14:50-15:10, Paper FrB08.5 | |
>Optimal Design of Control-Lyapunov Functions by Semi-Infinite Stochastic Programming (I) |
|
Tang, Wentao | NC State University |
Daoutidis, Prodromos | Univ. of Minnesota |
Keywords: Lyapunov methods, Nonlinear systems, Optimization
Abstract: Lyapunov-based control is a common method to enforce closed-loop stability of nonlinear systems, where the choice of a control-Lyapunov function has a strong impact on the resulting performance. In this paper, we propose a generic semi-infinite stochastic programming formulation for the optimal control-Lyapunov function design problem and discuss its various specializations. Specifically, the expected performance evaluated on simulated trajectories under different scenarios is optimized subject to infinite constraints on stability and performance specifications. A stochastic proximal primal-dual algorithm is introduced to find a stationary solution of such a semi-infinite stochastic programming problem. The proposed method is illustrated by a chemical reactor case study.
|
|
15:10-15:30, Paper FrB08.6 | |
>Data-Driven and Online Estimation of Linear Sensitivity Distribution Factors: A Low-Rank Approach |
|
Ospina, Ana M. | University of Colorado Boulder |
Dall'Anese, Emiliano | University of Colorado Boulder |
Keywords: Power systems, Smart grid, Optimization algorithms
Abstract: Estimation of sensitivity matrices in electrical transmission systems allows grid operators to evaluate in real-time how changes in power injections reflect into changes in power flows. In this paper, we propose a robust low-rank minimization approach to estimate sensitivity matrices based on measurements of power injections and power flows. An online proximal-gradient method is proposed to estimate sensitivities on-the-fly from real-time measurements. The proposed method obtains meaningful estimates with fewer measurements when the regression model is underdetermined, in contrast with existing methods based on least-squares approaches. In addition, our method can also identify faulty measurements and handle missing data. In this work, convergence results in terms of dynamic regret are presented. Numerical tests corroborate the effectiveness of the novel approach and the robustness of missing measurements and outliers.
|
|
FrB09 |
Simpor Junior 4811 |
Optimization III |
Regular Session |
Chair: Pu, Ye | The University of Melbourne |
Co-Chair: Dai, Ran | Purdue University |
|
13:30-13:50, Paper FrB09.1 | |
>Reinforcement Learning-Guided Quadratically Constrained Quadratic Programming for Enhanced Convergence and Optimality |
|
Chaoying, Pei | Purdue University |
Xu, Zhi | Purdue University |
You, Sixiong | Purdue University |
Sun, Jeffrey | Purdue University |
Dai, Ran | Purdue University |
Keywords: Optimization, Optimization algorithms, Learning
Abstract: In the context of Quadratically Constrained Quadratic Programming (QCQP) with dynamic parameters, the effectiveness of various optimization approaches is heavily influenced by the quality of the initial guess. To address this challenge, this paper proposes a novel approach that leverages reinforcement learning (RL) to generate high-performing initial guesses for iterative algorithms, with the dynamic parameters serving as inputs. Our approach aims to accelerate convergence and improve the objective value, thereby enabling efficient and effective solutions to the QCQP problem under variability. In this study, we evaluate the proposed approach by applying it to an iterative algorithm, specifically the Iterative Rank Minimization (IRM) algorithm. Our empirical evaluations demonstrate the efficacy of the proposed approach in solving QCQP problems with dynamic parameters. The RL-guided IRM algorithm yields high-quality solutions, as evidenced by significantly improved optimality and faster convergence when compared to the original IRM algorithm.
|
|
13:50-14:10, Paper FrB09.2 | |
>Ergodic Convergence Results for the Arrow–Hurwicz Differential System |
|
Niederlaender, Simon | Siemens AG |
Keywords: Optimization, Optimization algorithms, Lyapunov methods
Abstract: In a real Hilbert space setting, we investigate the ergodic convergence properties of the solutions of the classical Arrow–Hurwicz differential system in view of solving linearly constrained convex minimization problems. Under the convexity hypothesis on the objective function of the minimization problem, we recover the fact that every solution of the Arrow–Hurwicz differential system weakly converges in average towards its asymptotic center. Moreover, it is shown that the primal-dual gap function relative to an averaged solution obeys the asymptotic estimate mathcal{O}(1/t) as tto+infty. If, in addition, the linear operator associated with the constraint function of the minimization problem is bounded from below, we find that the primal-dual gap function obeys the refined asymptotic estimate mathcal{O}(1/t^{2}) as tto+infty. Numerical experiments illustrate our theoretical findings.
|
|
14:10-14:30, Paper FrB09.3 | |
>Multivariate Polynomial Optimization in Complex Variables Is a (Rectangular) Multiparameter Eigenvalue Problem |
|
Vermeersch, Christof | KU Leuven |
Lagauw, Sibren | KU Leuven |
De Moor, Bart L.R. | Katholieke Universiteit Leuven |
Keywords: Optimization, Optimization algorithms, Numerical algorithms
Abstract: We extend the relation between univariate polynomial optimization in one complex variable and the polynomial eigenvalue problem to the multivariate case. The first-order necessary conditions for optimality of the multivariate polynomial optimization problem, which are computed using Wirtinger derivatives, constitute a system of multivariate polynomial equations in the complex variables and their complex conjugates. Wirtinger calculus provides an elegant way to differentiate real-valued (cost) functions in complex variables. An elimination of the complex conjugate variables, via the Macaulay matrix, results in a (rectangular) multiparameter eigenvalue problem, (some of) the eigentuples of which correspond to the stationary points of the original real-valued cost function. We illustrate our novel globally optimal optimization approach with several (didactical) examples.
|
|
14:30-14:50, Paper FrB09.4 | |
>Linearized ADMM for Nonsmooth Nonconvex Optimization with Nonlinear Equality Constraints |
|
El Bourkhissi, Lahcen | University Polytechnic of Bucharest |
Necoara, Ion | University Politehnica Bucharest and Institute of Mathematical S |
Patrinos, Panagiotis | KU Leuven |
Keywords: Optimization, Optimization algorithms, Predictive control for nonlinear systems
Abstract: This paper proposes a new approach for solving a structured nonsmooth nonconvex optimization problem with nonlinear equality constraints, where both the objective function and constraints are 2-blocks separable. Our method is based on a 2-block linearized ADMM, where we linearize the smooth part of the cost function and the nonlinear term of the functional constraints in the augmented Lagrangian at each outer iteration. This results in simple subproblems, whose solutions are used to update the iterates of the 2 blocks variables. We prove global convergence for the sequence generated by our method to a stationary point of the original problem. To demonstrate its effectiveness, we apply our proposed algorithm as a solver for the nonlinear model predictive control problem of an inverted pendulum on a cart.
|
|
14:50-15:10, Paper FrB09.5 | |
>Tight Lower Bounds on the Convergence Rate of Primal-Dual Dynamics for Equality Constrained Convex Problems |
|
Ozaslan, Ibrahim Kurban | University of Southern California |
Jovanovic, Mihailo R. | University of Southern California |
Keywords: Optimization, Optimization algorithms, Stability of nonlinear systems
Abstract: We study the exponential stability of continuous-time primal-dual gradient flow dynamics for convex optimization problems with linear equality constraints. Without making any assumptions on the rank of the constraint matrix, we obtain a tight lower bound on the worst-case convergence rate for smooth strongly convex objective functions. Our analysis identifies two different convergence regimes depending on the ratio between primal and dual time scales. When the primal time scale is inversely proportional to the Lipschitz parameter of the objective function and the dual time scale is large enough, the convergence rate is inversely proportional to the condition number of the problem. In contrast to the existing results, our lower bound on the convergence rate does not depend on the condition number of the constraint matrix.
|
|
15:10-15:30, Paper FrB09.6 | |
>Second-Order Properties of Noisy Distributed Gradient Descent |
|
Qin, Lei | The University of Melbourne |
Cantoni, Michael | University of Melbourne |
Pu, Ye | The University of Melbourne |
Keywords: Optimization, Optimization algorithms
Abstract: We study a fixed step-size distributed gradient descent algorithm for solving optimization problems in which the objective is a finite sum of smooth but possibly non-convex functions. Random perturbations of the gradient descent directions are introduced at each step to actively evade saddle points. Under certain regularity conditions, and with a suitable step-size, it is established that each agent converges to a neighborhood of a local minimizer; the size of the neighborhood depends on the step-size and a probabilistic confidence parameter. A numerical example is presented to illustrate the effectiveness of the random perturbations in terms of escaping saddle points in fewer iterations than without the perturbations.
|
|
FrB10 |
Roselle Junior 4713 |
Learning I |
Regular Session |
Chair: Zeng, Shen | Washington University in St. Louis |
Co-Chair: Siami, Milad | Northeastern University |
|
13:30-13:50, Paper FrB10.1 | |
>An Iterative Approach to Safe Learning in Unknown Constrained Environments |
|
Vu, Minh | Washington University in St. Louis |
Zeng, Shen | Washington University in St. Louis |
Keywords: Learning, Constrained control, Autonomous systems
Abstract: This paper presents an iterative learning technique to safely guide a nonlinear system with unknown dynamics through an environment with unspecified constraints. The presented approach leverages the system’s local dynamics to incrementally explore the environment and learn the appropriate control, which allows us to avoid the data-intensive task of learning an accurate global system model. Due to the local nature of this approach, the system’s safe operating region does not need to be pre-specified as long as local areas of the constraints can be identified when the system approaches those areas. The functionality and efficiency of the proposed approach are demonstrated through simulation of a unicycle and a high-dimensional nonlinear quadcopter, indicating the system’s ability to learn dynamics from data and safely navigate unknown environments.
|
|
13:50-14:10, Paper FrB10.2 | |
>Optimal Containment Control of Nonlinear MASs: A Time-Aggregation-Based Policy Iteration Algorithm |
|
Shi, Xiongtao | Harbin Institute of Technology (Shenzhen) |
Li, Yanjie | Harbin Institue of Technology Shenzhen Graduate School |
Du, Chenglong | Central South University |
Keywords: Learning, Discrete event systems, Cooperative control
Abstract: In this paper, the optimal containment control of a class of unknown nonlinear multi-agent systems (MASs) is studied via a time-aggregation (TA) based model-free reinforcement learning (RL) algorithm. By proposing TA-based event-state, event-control, and integration-reward, the model-free TA-based policy iteration (TA-PI) approach is synthesized such that the policy evaluation and policy improvement steps are only executed for finite event-state, and the optimal control protocol is obtained with fewer computational requirements. Besides, the control input is intermittently updating only when the event-set is visited, which greatly reduce the updating frequency of control. Therefore, the proposed learning algorithm helps to save computational resources in both learning process and control updating. Moreover, armed with a finite predefined event-set, the developed TA-PI algorithm without employing function approximator and state discretization, resulting a strict convergence analysis via the mathematical induction. Finally, simulation results are given to show the feasibility and effectiveness of the proposed algorithm.
|
|
14:10-14:30, Paper FrB10.3 | |
>Multi-Task System Identification of Similar Linear Time-Invariant Dynamical Systems |
|
Chen, Yiting | University of Colorado Boulder |
Ospina, Ana M. | University of Colorado Boulder |
Pasqualetti, Fabio | University of California, Riverside |
Dall'Anese, Emiliano | University of Colorado Boulder |
Keywords: Learning, Identification, Optimization algorithms
Abstract: This paper presents a system identification framework - inspired by multi-task learning - to estimate the dynamics of a given number of linear time-invariant (LTI) systems jointly by leveraging structural similarities across the systems. In particular, we consider LTI systems that model networked systems with similar connectivity, or LTI systems with small differences in their matrices. The system identification task involves the minimization of the least-squares (LS) fit for individual systems, augmented with a regularization function that enforces structural similarities. The proposed method is particularly suitable for cases when the recorded trajectories for one or more LTI systems are not sufficiently rich, leading to ill-conditioning of LS methods. We analyze the performance of the proposed method when the matrices of the LTI systems feature a common sparsity pattern (i.e., similar connectivity), and provide simulations based on real data for the estimation of the brain dynamics. We show that the proposed method requires a significantly smaller number of fMRI scans to achieve similar error levels of the LS.
|
|
14:30-14:50, Paper FrB10.4 | |
>Derivative Feedback Control Using Reinforcement Learning |
|
Zaheer, Muhammad Hamad | University of New Hampshire |
Yoon, Se Young (Pablo) | University of New Hampshire |
Rizvi, Syed Ali Asad | Tennessee Technological University |
Keywords: Learning, Optimal control, Uncertain systems
Abstract: In this paper, the model-free state-derivative and output-derivative feedback control of continuous-time dynamic systems are considered. First, an online iterative algorithm is designed following the reinforcement learning framework, in which measurements of the system state derivatives are collected to synthesize an optimal state-derivative feedback control law. The proposed approach employs the integral reinforcement learning technique to iteratively solve a derivative feedback algebraic Riccati equation. The iterative algorithm is extended to the output-derivative feedback case by introducing a state-parametrization scheme that reconstructs the state-derivative signal from the output derivatives and input data. Based on this parametrization, we develop an online iterative algorithm based on the reinforcement learning framework to determine the optimal output-derivative feedback controller. Convergence of the iterative algorithms to the analytical optimal control solutions is demonstrated. Numerical simulations motivated by practical applications demonstrate the benefits of our method compared to the standard output feedback reinforcement learning algorithms.
|
|
14:50-15:10, Paper FrB10.5 | |
>Dynamics and Perturbations of Overparameterized Linear Neural Networks |
|
Castello Branco de Oliveira, Arthur | Northeastern University |
Siami, Milad | Northeastern University |
Sontag, Eduardo | Northeastern University |
Keywords: Learning, Optimization, Nonlinear systems
Abstract: Recent research in neural networks and machine learning suggests that using many more parameters than strictly required by the initial complexity of a regression problem can result in more accurate or faster-converging models -- contrary to classical statistical belief. This phenomenon, sometimes referred to as "benign overfitting", raises questions regarding in what other ways might overparameterization affect the properties of a learning problem. In this work, we investigate the effects of overfitting on the robustness of gradient-descent training when subject to uncertainty on the gradient estimation, which arises naturally if the gradient is estimated from noisy data or directly measured. Our object of study is a linear neural network with a single, arbitrarily wide, hidden layer and an arbitrary number of inputs and outputs, which can be equivalently written as an overparameterized matrix factorization problem. In this paper we solve the problem for the case where the input and output of our neural network are one-dimensional, deriving sufficient conditions for the robustness of our system based on necessary and sufficient conditions for convergence in the undisturbed case. We then show that the general overparameterized formulation introduces a set of spurious equilibria that lay outside the set where the loss function is minimized, and discuss directions of future work that might extend our current results for more general settings.
|
|
15:10-15:30, Paper FrB10.6 | |
>Convergence of Gradient-Based MAML in LQR |
|
Musavi, Negin | University of Illinois Urbana Champaign |
Dullerud, Geir E. | Univ of Illinois, Urbana-Champaign |
Keywords: Learning, Optimization, Optimal control
Abstract: The main objective of this research paper is to investigate the local convergence characteristics of Model-agnostic Meta-learning (MAML) when applied to linear system quadratic optimal control (LQR). MAML and its variations have become popular techniques for quickly adapting to new tasks by leveraging previous learning knowledge in areas like regression, classification, and reinforcement learning. However, its theoretical guarantees remain unknown due to non-convexity and its structure, making it even more challenging to ensure stability in the dynamic system setting. This study focuses on exploring MAML in the LQR setting, providing its local convergence guarantees while maintaining the stability of the dynamical system. The paper also presents simple numerical results to demonstrate the convergence properties of MAML in LQR tasks.
|
|
FrB11 |
Roselle Junior 4712 |
Large-Scale Systems II |
Regular Session |
Chair: Tegling, Emma | Lund University |
Co-Chair: Stefansson, Elis | KTH Royal Institute of Technology |
|
13:30-13:50, Paper FrB11.1 | |
>Multi-UAV Trajectory Planning Problem Using the Difference of Convex Function Programming |
|
Ngo, Anh Phuong | North Carolina A&T State University |
Thomas, Christan | Lockheed Martin Corporation |
Karimoddini, Ali | North Carolina A&T State University |
Nguyen, Hieu | North Carolina Agricultural and Technical State University |
Keywords: Air traffic management, Computational methods, Numerical algorithms
Abstract: Trajectory planning for a swarm of UAVs is known as a challenging nonconvex optimization problem, particularly due to a large number of collision avoidance constraints required for individual pairs of UAVs in the swarm. In this paper, we tackle this nonconvexity by leveraging the difference of convex function (DC) programming. We introduce the slack variables to relax and reformulate the collision avoidance conditions and employ the penalty function term to equivalently convert the problem into the DC form. Consequently, we construct a penalty DC algorithm in which we sequentially solve a set of convex optimization problems obtained by linearizing the collision avoidance constraint. The algorithm iteratively tightens the safety condition and reduces the objective cost of the planning problem and the additional penalty term. Numerical results demonstrate the effectiveness of the proposed approach in planning a large number of UAVs in congested space.
|
|
13:50-14:10, Paper FrB11.2 | |
>New Formal Descriptions for Timed Coloured Petri Nets Using Formal Series |
|
Bal dit Sollier, Louis | ENS Paris-Saclay, EDF R&D |
Ourghanlian, Alain | Edf R&d Chatou |
Amari, Saïd | LURPA - Ecole Normale Paris Saclay |
Keywords: Petri nets
Abstract: This paper proposes to introduce a dioid of coloured formal series for the description of Timed Coloured Petri Nets (TCPN). These formal series allow us to express TCPN time/event shiftings. As coloured Petri nets can reach a high level of complexity, we first present the coloured formal series for linear systems. Nonetheless, we extend our work to the time and event shiftings in a conflict situation. This example shows the powerful expressiveness of these series and that we can build configurable models for which the transfer function computation can be automated via predictability assumptions.
|
|
14:10-14:30, Paper FrB11.3 | |
>Efficient and Reconfigurable Optimal Planning in Large-Scale Systems Using Hierarchical Finite State Machines (I) |
|
Stefansson, Elis | KTH Royal Institute of Technology |
Johansson, Karl H. | KTH Royal Institute of Technology |
Keywords: Automata, Hierarchical control, Large-scale systems
Abstract: In this paper, we consider a planning problem for a large-scale system modelled as a hierarchical finite state machine (HFSM) and develop a control algorithm for computing optimal plans between any two states. The control algorithm consists of two steps: a preprocessing step computing optimal exit costs for each machine in the HFSM, with time complexity scaling linearly with the number of machines, and a query step that rapidly computes optimal plans, truncating irrelevant parts of the HFSM using the optimal exit costs, with time complexity scaling near-linearly with the depth of the HFSM. The control algorithm is reconfigurable in the sense that a change in the HFSM is efficiently handled, updating only needed parts in the preprocessing step to account for the change, with time complexity linear in the depth of the HFSM. We validate our algorithm on a robotic application, comparing it with Dijkstra's algorithm and Contraction Hierarchies. Our algorithm outperforms both.
|
|
14:30-14:50, Paper FrB11.4 | |
>A Closed-Loop Design for Scalable High-Order Consensus |
|
Hansson, Jonas | Lund University |
Tegling, Emma | Lund University |
Keywords: Decentralized control, Distributed control, Large-scale systems
Abstract: This paper studies the problem of coordinating a group of nth-order integrator systems. As in the well-studied conventional consensus problem, we consider linear and distributed control with only local and relative measurements. We propose a closed-loop dynamic that we call serial consensus and prove it achieves nth-order consensus regardless of model order and underlying network graph. This alleviates an important scalability limitation in conventional consensus dynamics of order n >= 2, whereby they may lose stability if the underlying network grows. The distributed control law which achieves the desired closed loop dynamics is shown to be localized and obey the limitation to relative state measurements. Furthermore, through use of the small-gain theorem, the serial consensus system is shown to be robust to both model and feedback uncertainties. We illustrate the theoretical results through examples.
|
|
14:50-15:10, Paper FrB11.5 | |
>Controlling Identical Linear Multi-Agent Systems Over Directed Graphs |
|
Zaupa, Nicola | LAAS, CNRS |
Zaccarian, Luca | LAAS-CNRS |
Tarbouriech, Sophie | LAAS-CNRS |
Queinnec, Isabelle | LAAS-CNRS |
Giordano, Giulia | University of Trento |
Keywords: Decentralized control, LMIs, Linear systems
Abstract: We consider the problem of synchronizing a multi-agent system (MAS) composed of several identical linear systems connected through a directed graph. To design a suitable controller, we construct conditions based on Bilinear Matrix Inequalities (BMIs) that ensure state synchronization. Since these conditions are non-convex, we propose an iterative algorithm based on a suitable relaxation that allows us to formulate Linear Matrix Inequality (LMI) conditions. As a result, the algorithm yields a common state-feedback matrix for the controller that satisfies general linear performance constraints. Our results are achieved under the mild assumption that the graph is time-invariant and connected.
|
|
15:10-15:30, Paper FrB11.6 | |
>Quantification of Distributionally Robust Risk of Cascade of Failures in Platoon of Vehicles (I) |
|
Pandey, Vivek | Lehigh University |
Liu, Guangyi | Lehigh University |
Amini, Arash | The University of Texas at Austin |
Motee, Nader | Lehigh University |
Keywords: Networked control systems, Stochastic systems, Delay systems
Abstract: Achieving safety is a critical aspect of attaining autonomy in a platoon of autonomous vehicles. In this paper, we propose a distributionally robust risk framework to investigate cascading failures in platoons. To examine the impact of network connectivity and system dynamics on the emergence of cascading failures, we consider a time-delayed network model of the platoon of vehicles as a benchmark. To study the cascading effects among pairs of vehicles in the platoon, we use the measure of conditional distributionally robust functional. We extend the risk framework to quantify cascading failures by utilizing a bi-variate normal distribution. Our work establishes closed-form risk formulas that illustrate the effects of time-delay, noise statistics, underlying communication graph, and sets of soft failures. The insights gained from our research can be applied to design safe platoons that are robust to the risk of cascading failures. We validate our results through extensive simulations.
|
|
FrB12 |
Roselle Junior 4711 |
Distributed Control II |
Regular Session |
Chair: Watson, Jeremy | University of Canterbury |
Co-Chair: van Dijk, Stefan | Technical University of Eindhoven |
|
13:30-13:50, Paper FrB12.1 | |
>State Aggregation for Distributed Value Iteration in Dynamic Programming |
|
Vertovec, Nikolaus | University of Oxford |
Margellos, Kostas | University of Oxford |
Keywords: Distributed control, Large-scale systems, Traffic control
Abstract: We propose a distributed algorithm to solve a dynamic programming problem with multiple agents, where each agent has only partial knowledge of the state transition probabilities and costs. We provide consensus proofs for the presented algorithm and derive error bounds of the obtained value function with respect to what is considered as the "true solution" obtained from conventional value iteration. To minimize communication overhead between agents, state costs are aggregated and shared between agents only when the updated costs are expected to influence the solution of other agents significantly. We demonstrate the efficacy of the proposed distributed aggregation method to a large-scale urban traffic routing problem. Individual agents compute the fastest route to a common access point and share local congestion information with other agents allowing for fully distributed routing with minimal communication between agents.
|
|
13:50-14:10, Paper FrB12.2 | |
>Real-Time Deep-Learning-Driven Parallel MPC |
|
Kohút, Roman | Slovak University of Technology in Bratislava |
Pavlovičová, Erika | Slovak University of Technology in Bratislava |
Fedorová, Kristína | Slovak University of Technology in Bratislava |
Oravec, Juraj | Slovak University of Technology in Bratislava |
Kvasnica, Michal | Slovak University of Technology in Bratislava |
Keywords: Distributed control, Machine learning, Predictive control for linear systems
Abstract: A novel real-time approximated MPC control policy based on deep learning is proposed to address the high computational burden of model predictive control (MPC) for large-scale systems and those with fast dynamics. This control method approximates the optimal solution of the distributed optimization problems in the ALADIN-based parallel MPC design framework, resulting in a highly effective approach that outperforms other well-known methods for solving the MPC design problem. The numerical case study shows promising results, demonstrating the potential of this approach for real-time implementation.
|
|
14:10-14:30, Paper FrB12.3 | |
>Local Input-To-State Stability for Consensus in the Presence of Intermittent Communication and Input Saturation |
|
Silva, Thales C. | University of Pennsylvania |
Hsieh, M. Ani | University of Pennsylvania |
Keywords: Distributed control, Networked control systems, LMIs
Abstract: This paper addresses the problem of reaching consensus under input saturation and intermittent communication, which can hinder the convergence of the system. We propose a method that translates the consensus into an equivalent stability problem. Then, we compute bounded sets that enclose the initial conditions and the evolution of trajectories leading to local input-to-state stability for systems interconnected over directed intermittent topologies. Our contributions include sufficient conditions for stability and stabilization of multi-agent systems under intermittent interactions and saturating inputs, with the ability to evaluate disturbance tolerance and rejection based on the regions that enclose the system’s trajectories. We define disturbance rejection in terms of the L2 gain, and formulate stability and controller design conditions as convex optimization problems. Our method enable the maximization of regions that ensure local input-to-state stability, we provide numerical examples highlighting the trade-offs between mean frequency of intermittent interactions, disturbance energy, and convergence region size.
|
|
14:30-14:50, Paper FrB12.4 | |
>Decentralized Design for LQ Consensus in Multi-Agent Systems |
|
van Dijk, Stefan | Technical University of Eindhoven |
Chanfreut, Paula | Eindhoven University of Technology |
Heemels, W.P.M.H. | Eindhoven University of Technology |
Keywords: Distributed control, Optimal control, Decentralized control
Abstract: Consensus control of multi-agent systems (MAS) with integrator dynamics is a canonical and well-studied prob- lem in the literature. In contrast, the optimal distributed linear quadratic (LQ) consensus problem minimizing an appropriate quadratic cost is less studied. For this problem, most of the available design methods require global information on the interconnection graph and/or global (initial) state information. In this paper, we propose a suboptimal solution to the LQ-based distributed consensus control problem by approximating the quadratic cost function in a way that allows for decentralized design of the control gains. The resulting control protocol only uses information from neighboring agents for both control design and implementation. It has the additional benefit that the information needs to be only exchanged periodically, reducing the communication requirements of the agent. Despite the sub- optimality, asymptotic consensus is guaranteed for our control law, as we will formally prove. We illustrate by numerical simulations on a 6-agent system the effectiveness of our design and compare it to other approaches.
|
|
14:50-15:10, Paper FrB12.5 | |
>Linear Quadratic Leader-Following Consensus of Multi-Agent Systems: A Decentralized Computation and Distributed Information Fusion Strategy |
|
Ren, Yunxiao | Peking University |
Qian, Jiachen | Peking University |
Duan, Zhisheng | Peking University |
Keywords: Distributed control, Optimal control, Networked control systems
Abstract: This study delves into the leader-following consensus problem in linear multi-agent systems that are structured on weight-balanced digraphs. The primary aim is to formulate a distributed, implementable optimal controller capable of achieving both leader consensus and simultaneous optimization of the linear quadratic cost function. To attain this objective, we introduce a decentralized computation approach and advocate for a distributed information strategy. Initially, the computation of the global Riccati equation is disassembled into the computation of local Riccati equations. Following that, we propose an information fusion algorithm utilizing the dynamic average consensus approach to unravel the optimal controller, enabling its implementation in a distributed fashion. Additionally, we offer numerical simulation examples to demonstrate the efficacy of our proposed approach.
|
|
15:10-15:30, Paper FrB12.6 | |
>Discrete-Time Distributed Optimization for Linear Uncertain Multi-Agent Systems |
|
Liu, Tong | New York University |
Bin, Michelangelo | University of Bologna |
Notarnicola, Ivano | University of Bologna |
Parisini, Thomas | Imperial College & Univ. of Trieste |
Jiang, Zhong-Ping | New York University |
Keywords: Distributed control, Optimization, Uncertain systems
Abstract: The distributed optimization algorithm proposed by J. Wang and N. Elia in 2010 has been shown to achieve linear convergence for multi-agent systems with single-integrator dynamics. This paper extends their result, including the linear convergence rate, to a more complex scenario where the agents have heterogeneous multi-input multi-output linear dynamics and are subject to external disturbances and parametric uncertainties. Disturbances are dealt with via an internal-model-based control design, and the interaction among the tracking error dynamics, average dynamics, and dispersion dynamics is analyzed through a composite Lyapunov function and the cyclic small-gain theorem. The key is to ensure a small enough stepsize for the convergence of the proposed algorithm, which is similar to the condition for time-scale separation in singular perturbation theory.
|
|
FrB13 |
Roselle Junior 4613 |
Networked Systems |
Regular Session |
Chair: Zhang, Yuan | School of Automation, Beijing Institute of Technology |
Co-Chair: Hurst, Winston | University of California, Santa Barbara |
|
13:30-13:50, Paper FrB13.1 | |
>Stability of Non-Cooperative Load Balancing with Time-Varying Latency |
|
Giuseppi, Alessandro | University of Rome "La Sapienza" |
Menegatti, Danilo | DIAG, Università Degli Studi Di Roma La Sapienz |
Pietrabissa, Antonio | University of Rome "La Sapienza" |
Keywords: Control of networks, Switched systems, Network analysis and control
Abstract: The problem of non-cooperative load balancing arises in multi-agent scenarios where users/services compete for some limited resources. This study, leveraging on results from set stability and switched systems control theory, analyses the convergence properties of a class of load-balancing strategies towards a set of approximated adversarial equilibria in a scenario in which the performance of the resource providers is described by a time-varying latency function.
|
|
13:50-14:10, Paper FrB13.2 | |
>Optimal Dynamic Trajectories for UAVs in Mobility-Enabled Relay System |
|
Hurst, Winston | University of California, Santa Barbara |
Mostofi, Yasamin | Univ. of California Santa Barbara |
Keywords: Control over communications, Markov processes, Machine learning
Abstract: We consider a UAV which acts as a mobile relay and must plan a trajectory to enable data transfer between multiple pairs of communication nodes. For each pair, successful data transfer is only possible in non-convex regions (relay regions) where a given quality of service requirement may be satisfied for both nodes. Trajectories consist of 1) locations where the UAV stops to relay (relay positions) and 2) a dynamic transition policy which determines the sequence in which the pairs are serviced. We are interested in minimizing the average time a bit waits at a source before being sent to a destination and first pose a general, non-convex problem that calls for optimization over both the relay positions and the dynamic transition policy. To find approximate solutions, we formulate an average cost semi-Markov decision process and propose a deep-reinforcement-learning-based algorithm to solve it. To validate our approach, we present the results of several simulation experiments, which show our approach significantly outperforms the state-of-the-art.
|
|
14:10-14:30, Paper FrB13.3 | |
>Towards Minimal Data Rate Enforcing Regular Safety Properties: An Invariance Entropy Approach |
|
Tomar, Mahendra Singh | BITS Pilani K K Birla Goa Campus |
Zamani, Majid | University of Colorado Boulder |
Keywords: Control over communications, Networked control systems, Hybrid systems
Abstract: The study of minimal data rate for control using some notions of entropy has been so far limited to classical control tasks such as set invariance, state-estimation, or stabilization. In this work, for the first time, we present a study on sufficient data rates to enforce regular safety properties over uncertain systems with dynamics described by set valued maps. Every regular safety property has a set of bad prefixes which can be modelled by a deterministic finite automaton (DFA). The main idea is to construct a hybrid system by taking the product of the deterministic finite automata with the given system and studying the invariance feedback entropy (IFE) of controlled invariant sets of the hybrid system. If there exists a nonempty controlled invariant set for the hybrid system satisfying a certain property then there exists a coder-controller with a data rate not less than the IFE that can enforce the regular safety property over the original control system. We demonstrate the effectiveness of our results by designing a coder-controller enforcing a regular safety property over a linear control system.
|
|
14:30-14:50, Paper FrB13.4 | |
>Faster Consensus Via a Sparser Controller |
|
Ballotta, Luca | University of Padova |
Gupta, Vijay | Purdue University |
Keywords: Control system architecture, Delay systems, Distributed control
Abstract: In this paper, we investigate the architecture of an optimal controller that maximizes the convergence speed of a consensus protocol with single-integrator dynamics. Under the assumption that communication delays increase with the number of hops from which information is allowed to reach each agent, we address the optimal control design under delayed feedback and show that the optimal controller features, in general, a sparsely connected architecture.
|
|
14:50-15:10, Paper FrB13.5 | |
>Observability Blocking for Functional Privacy of Linear Dynamic Networks |
|
Zhang, Yuan | School of Automation, Beijing Institute of Technology |
Cheng, Ranbo | Beijing Institute of Technology |
Xia, Yuanqing | Beijing Institute of Technology |
Keywords: Control Systems Privacy, Network analysis and control, Observers for Linear systems
Abstract: This paper addresses the problem of determining the minimum set of state variables in a network that need to be blocked from direct measurements in order to protect functional privacy with respect to any output matrices. More precisely, the goal is to prevent adversarial observers or eavesdroppers from inferring a linear functional of states, either vector-wise or entry-wise. We relate the considered functional privacy to the concept of functional observability. Building on a PBH-like criterion for functional observability, we prove that both problems are NP-hard. However, by assuming a reasonable constant bound on the geometric multiplicities of the system's eigenvalues, we present an exact algorithm with polynomial time complexity for the vector-wise functional privacy protection problem. Based on this algorithm, we then provide a greedy algorithm for the entry-wise privacy protection problem. Finally, we provide an example to demonstrate the effectiveness of our proposed approach.
|
|
15:10-15:30, Paper FrB13.6 | |
>Differentially Private Stochastic Convex Optimization for Network Routing Applications |
|
Tsao, Matthew | Stanford University |
Gopalakrishnan, Karthik | Stanford University |
Yang, Kaidi | National University of Singapore |
Pavone, Marco | Stanford University |
Keywords: Control Systems Privacy, Transportation networks, Optimization
Abstract: Network routing problems are common across many engineering applications. Computing optimal routing policies requires knowledge about network demand, i.e., the origin and destination (OD) of all requests in the network. However, privacy considerations make it challenging to share individual OD data that would be required for computing optimal policies. Privacy can be particularly challenging in standard network routing problems because sources and sinks can be easily identified from flow conservation constraints, making feasibility and privacy mutually exclusive. In this paper, we present a differentially private algorithm for network routing problems. The main ingredient is a reformulation of network routing which moves all user data-dependent parameters out of the constraint set and into the objective function. We then present an algorithm for solving this formulation based on a differentially private variant of stochastic gradient descent. In this algorithm, differential privacy is achieved by injecting noise, and one may wonder if this noise injection compromises solution quality. We prove that our algorithm is both differentially private and asymptotically optimal as the size of the training set goes to infinity. We corroborate the theoretical results with numerical experiments on a road traffic network which show that our algorithm provides differentially private and near-optimal solutions in practice.
|
|
FrB14 |
Roselle Junior 4612 |
Observers for Nonlinear Systems I |
Regular Session |
Chair: Yong, Sze Zheng | Northeastern University |
Co-Chair: Postoyan, Romain | CNRS, CRAN, Université De Lorraine |
|
13:30-13:50, Paper FrB14.1 | |
>A Note on Observability of Nonlinear Discrete-Time Systems |
|
Kaldmäe, Arvo | Tallinn University of Technology |
Kotta, Ülle | Tallinn University of Technology |
Keywords: Observers for nonlinear systems, Algebraic/geometric methods, Nonlinear systems
Abstract: A concept of backward observability is introduced for nonlinear discrete-time control systems. According to the new definition the state variables can be expressed as functions of inputs, outputs and their backward shifts. It is shown that the new observability definition is more general for non-reversible systems than the one used typically in the literature. In case of reversible systems it is proved that backward observability is equivalent to the standard definition of observability. The new definition allows to enlarge the class of systems for which state variables can be estimated and the observers constructed.
|
|
13:50-14:10, Paper FrB14.2 | |
>An Adaptive Observer for Time-Varying Nonlinear Systems - Application to a Crop Irrigation Model |
|
Dadjo, Mahugnon Gildas | MISTEA, Univ. Montpellier, INRAE, Institut Agro and Inria, Univ |
Efimov, Denis | Inria |
Harmand, Jérome | INRA |
Rapaport, Alain | INRAE & Univ. Montpellier |
Ushirobira, Rosane | Inria |
Keywords: Observers for nonlinear systems, Estimation, Lyapunov methods
Abstract: We propose an adaptive observer for a class of nonlinear time-varying systems, for which the regressor depends not only on the known input-output signals but also on all the unmeasured states. There are state disturbances, and measurements are corrupted by noise. The Lyapunov function method is used to prove that the coupled system-observer dynamics admits a state-independent input-to-output stability property in estimation errors from unknown inputs. Numerical simulations illustrate the presented approach on a three-dimensional crop irrigation model.
|
|
14:10-14:30, Paper FrB14.3 | |
>A Masking Protocol for Private Communication and Attack Detection in Nonlinear Observers |
|
Cecilia, Andreu | Universitat Politècnica De Catalunya |
Astolfi, Daniele | Cnrs - Lagepp |
Casadei, Giacomo | Ecole Centrale Lyon |
Costa-Castelló, Ramon | Universitat Politècnica De Catalunya (UPC) |
Nesic, Dragan | University of Melbourne |
Keywords: Observers for nonlinear systems, Communication networks, Fault detection
Abstract: This work presents a novel masking protocol to secure the communication between a nonlinear plant and a nonlinear observer. Communication is secured in two senses. First, the privacy of the plant is preserved during the communication. Second, the protocol can detect a false-data injection attack in the communication link. The masking protocol is based on the use of washout-filters in nonlinear observers and the internal model principle.
|
|
14:30-14:50, Paper FrB14.4 | |
>Design of a Nonlinear Observer for a Class of Locally Lipschitz Systems by Using Input-To-State Stability: An LMI Approach |
|
Mohite, Shivaraj | PhD Student, University of Lorraine |
Alma, Marouane | CRAN Lorraine University |
Zemouche, Ali | CRAN UMR CNRS 7039 & Inria: EPI-DISCO |
Keywords: Observers for nonlinear systems, LMIs, Estimation
Abstract: This note addresses the problem of state estimation for a class of locally Lipschitz nonlinear systems under the effect of noise/disturbances. An observer structure based on Hilbert projection is used to handle the same class of nonlinearities. The boundedness of the state estimation error of the proposed observer is guaranteed by deploying the input-to-state stability (ISS) property. Based on ISS stability criterion, the new LMI condition is derived by combining a well-known LPV approach with a variant of Young inequality and novel matrix multipliers. The proposed LMIs have more decision variables than the methodologies presented in the literature, which provides extra degrees of freedom, and hence enhances LMI feasibility. Further, the effectiveness of the developed approach is highlighted through a numerical example. The performance of the observer is validated through the application of slip angle estimation in a nonlinear autonomous vehicle.
|
|
14:50-15:10, Paper FrB14.5 | |
>Interval Observers for Hybrid Dynamical Systems with Known Jump Times |
|
Pati, Tarun | Northeastern University |
Khajenejad, Mohammad | University of California, San Diego |
Daddala, Sai Praveen | Arizona State University |
Sanfelice, Ricardo G. | University of California at Santa Cruz |
Yong, Sze Zheng | Northeastern University |
Keywords: Observers for nonlinear systems, Hybrid systems
Abstract: This paper proposes a novel asymptotically stable interval estimator design for hybrid systems with nonlinear dynamics and observations under the assumption of known jump times. The proposed architecture leverages the concepts of mixed-monotone decompositions to construct a hybrid interval observer that is guaranteed to frame the true states (i.e., is correct) by construction. Moreover, using Lyapunov analysis and the positive system property of the framer error dynamics, we propose two approaches for computing the observer gains to achieve asymptotic stability of the error system based on mixed-integer semidefinite and linear programs. Further, our observer design incorporates additional degrees of freedom that may provide some advantages similar to coordinate transformations. Finally, we demonstrate the efficacy of the proposed hybrid observer design using two illustrative examples.
|
|
15:10-15:30, Paper FrB14.6 | |
>State Estimation for Enhanced Low Dimensional Electrochemical Models of Lithium-Ion Batteries |
|
Khalil, Mira | Université De Lorraine |
Postoyan, Romain | CNRS, CRAN, Université De Lorraine |
Raël, Stéphane | Université De Lorraine |
Keywords: Observers for nonlinear systems, Modeling, Energy systems
Abstract: Safe and efficient operation of lithium-ion batteries requires an accurate estimation of the internal states. One approach is to design an observer based on an electrochemical model of the battery internal dynamics. However, electrochemical models, and their associated observers, typically require a high dimension to generate accurate variables. In this paper, we explain how to alleviate this limitation by correcting the lithium concentrations generated by a finite-dimensional electrochemical model derived from the spatial discretizations of partial differential equations (PDE). We show that the corrected concentrations asymptotically match those generated by the original PDEs for constant input currents, irrespectively of the order of the considered finite-dimensional model. We then exploit this fact to derive a new state space model for which we design an observer, whose global, robust convergence is supported by a Lyapunov analysis provided a linear matrix inequality holds. The estimated concentrations are then corrected to asymptotically match those of the original PDEs in absence of disturbances for constant currents. Simulation results show improvements both in terms of modeling and estimation accuracy as a result of the proposed corrections.
|
|
FrB15 |
Roselle Junior 4611 |
Resilient Control Systems |
Regular Session |
Chair: Wen, Changyun | Nanyang Tech. Univ |
Co-Chair: Mallmann-Trenn, Frederik | King's College London |
|
13:30-13:50, Paper FrB15.1 | |
>Resilient Temporal Logic Planning in the Presence of Robot Failures |
|
Kalluraya, Samarth | Washington University in St. Louis |
Pappas, George J. | University of Pennsylvania |
Kantaros, Yiannis | Washington University in St. Louis |
Keywords: Resilient Control Systems, Autonomous robots, Automata
Abstract: Several task and motion planning algorithms have been proposed recently to design paths for mobile robot teams with collaborative high-level missions specified using formal languages, such as Linear Temporal Logic (LTL). However, the designed paths often lack reactivity to failures of robot capabilities (e.g., sensing, mobility, or manipulation) that can occur due to unanticipated events (e.g., human intervention or system malfunctioning) which in turn may compromise mission performance. To address this novel challenge, in this paper we propose a new resilient mission planning algorithm for teams of heterogeneous robots with collaborative LTL missions. The robots are heterogeneous with respect to their capabilities while the mission requires applications of these skills at certain areas in the environment in a temporal/logical order. The proposed method designs paths that can adapt to unexpected failures of robot capabilities. This is accomplished by re-allocating sub-tasks to the robots based on their currently functioning skills while minimally disrupting the existing team motion plans. We provide experiments and theoretical guarantees demonstrating the efficiency and resiliency of the proposed algorithm.
|
|
13:50-14:10, Paper FrB15.2 | |
>Reinforcement Learning-Based Optimal Control and Software Rejuvenation for Safe and Efficient UAV Navigation |
|
Chen, Angela | Carnegie Mellon University |
Mitsopoulos, Konstantinos | Institute for Human and Machine Cognition |
Romagnoli, Raffaele | Carnegie Mellon University |
Keywords: Resilient Control Systems, Machine learning, Autonomous vehicles
Abstract: Unmanned autonomous vehicles (UAVs) rely on effective path planning and tracking control to accomplish complex tasks in various domains. Reinforcement Learning (RL) methods are becoming increasingly popular in control applications, as they can learn from data and deal with unmodelled dynamics. Cyber-physical systems (CPSs), such as UAVs, integrate sensing, network communication, control, and computation to solve challenging problems. In this context, Software Rejuvenation (SR) is a protection mechanism that refreshes the control software to mitigate cyber-attacks, but it can affect the tracking controller's performance due to discrepancies between the control software and the physical system state. Traditional approaches to mitigate this effect are conservative, hindering the overall system performance. In this paper, we propose a novel approach that incorporates Deep Reinforcement Learning (Deep RL) into SR to design a safe and high-performing tracking controller. Our approach optimizes safety and performance, and we demonstrate its effectiveness during UAV simulations. We compare our approach with traditional methods and show that it improves the system's performance while maintaining safety constraints. Our approach takes 10 seconds less to reach the goal and we interpret this enhancement through a p-norm analysis.
|
|
14:10-14:30, Paper FrB15.3 | |
>Resilient Containment Control of Multi-Agent Networks in Adversarial Environment |
|
Kuo, Chan-Yuan | Purdue University |
Du, Bin | Nanjing University of Aeronautics and Astronautics |
Sun, Dengfeng | Purdue University |
Keywords: Resilient Control Systems, Networked control systems, Fault tolerant systems
Abstract: We study the problem of containment control in an adversarial environment, where some of the agents may be adversarial. We identify the security issue of a containment control protocol in such adversarial environment. We propose a resilient containment control protocol that ensures the state of each non-adversarial (normal) follower agent converges to the convex hull spanned by the states of the normal leader agents. Specifically, our protocol is based on the method of resilient convex combination and works for agents with a vector state. For multi-agent networks consisting of one follower agent and multiple leaders, we provide a sufficient condition on the communication topology that guarantees the success of our proposed protocol. In addition, we provide a set of numerical simulations to demonstrate the success of our protocol and verify our theoretical results.
|
|
14:30-14:50, Paper FrB15.4 | |
>Resilient Synchronization of Networked Euler-Lagrangian Systems in Adversarial Environments |
|
Chen, Hongjian | Nanyang Technological University |
Li, Xiaolei | Yanshan University |
Wen, Changyun | Nanyang Tech. Univ |
Fang, Xu | KTH Royal Institute of Technology |
Keywords: Resilient Control Systems, Nonlinear systems, Distributed control
Abstract: This paper considers the resilient synchronization problems of multiple Euler-Lagrange (EL) systems, where the communication network is affected by the external attacks or internal non-participant agents. The considered adversarial environments can cover several types of cyber-attacks, such as misbehaving agents and false data injection attacks. The remaining normal agents aim to reach a common decision despite the influence of faulty agents. To this end, a ``safe kernel” based secure control scheme is proposed for the networked Lagrangian systems. According to the scheme, each healthy agent generates a convex hull based on the states of its neighbors and updates its reference state toward this kernel only in each sampling instant to reduce the computational burden. The ``average sampling interval” is used to define the number of sampling instants for faster convergence. With an assumption on the number of misbehaving agents, the proposed scheme guarantees consensus of Euler-Lagrange systems even in adversarial environments. Mathematical proofs and a numerical example are presented to verify the resilience and validity of the proposed scheme.
|
|
14:50-15:10, Paper FrB15.5 | |
>Dynamic Crowd Vetting: Collaborative Detection of Malicious Robots in Dynamic Communication Networks |
|
Cavorsi, Matthew | Harvard University |
Mallmann-Trenn, Frederik | King's College London |
Saldana, David | Lehigh University |
Gil, Stephanie | Harvard University |
Keywords: Resilient Control Systems, Robotics, Distributed control
Abstract: Coordination in a large number of networked robots is a challenging task, especially when robots are constantly moving around the environment and there are malicious attacks within the network. Various approaches in the literature exist for detecting malicious robots, such as message sampling or suspicious behavior analysis. However, these approaches require every robot to sample every other robot in the network, leading to a slow detection process that degrades team performance. This paper introduces a method that significantly decreases the detection time for legitimate robots to identify malicious robots in a scenario where legitimate robots are randomly moving around the environment. Our method leverages the concept of "Dynamic Crowd Vetting" by utilizing observations from random encounters and trusted neighboring robots' opinions to quickly improve the accuracy of detecting malicious robots. The key intuition is that as long as each legitimate robot accurately estimates the legitimacy of at least some fixed subset of the team, the second-hand information they receive from trusted neighbors is enough to correct any misclassifications and provide accurate trust estimations of the rest of the team. We show that the size of this fixed subset can be characterized as a function of fundamental graph and random walk properties. Furthermore, we formally show that as the number of robots in the team increases the detection time remains constant. We develop a closed form expression for the critical number of time-steps required for our algorithm to successfully identify the true legitimacy of each robot to within a specified failure probability. Our theoretical results are validated through simulations demonstrating significant reductions in detection time when compared to previous works that do not leverage trusted neighbor information.
|
|
15:10-15:30, Paper FrB15.6 | |
>A Compositional Resilience Index for Computationally Efficient Safety Analysis of Interconnected Systems (I) |
|
Niu, Luyao | University of Washington |
Maruf, Abdullah Al | University of Washington |
Clark, Andrew | Washington University in St. Louis |
Mertoguno, Sukarno | Georgia Institute of Technology |
Poovendran, Radha | University of Washington |
Keywords: Resilient Control Systems, Nonlinear systems, Cyber-Physical Security
Abstract: Interconnected systems such as power systems and chemical processes are often required to satisfy safety properties in the presence of faults and attacks. Verifying safety of these systems, however, is computationally challenging due to nonlinear dynamics, high dimensionality, and combinatorial number of possible faults and attacks that can be incurred by the subsystems interconnected within the network. In this paper, we develop a compositional resilience index to verify safety properties of interconnected systems under faults and attacks. The resilience index is a tuple serving the following two purposes. First, it quantifies how a safety property is impacted when a subsystem is compromised by faults and attacks. Second, the resilience index characterizes the needed behavior of a subsystem during normal operations to ensure safety violations will not occur when future adverse events occur. We develop a set of sufficient conditions on the dynamics of each subsystem to satisfy its safety constraint, and leverage these conditions to formulate an optimization program to compute the resilience index. When multiple subsystems are interconnected and their resilience indices are given, we show that the safety constraints of the interconnected system can be efficiently verified by solving a system of linear inequalities. We demonstrate our developed resilience index using a numerical case study on chemical reactors connected in series.
|
|
FrB16 |
Peony Junior 4512 |
Emerging Control Applications |
Regular Session |
Chair: Prandini, Maria | Politecnico Di Milano |
Co-Chair: Karlsson, Niklas | Amazon |
|
13:30-13:50, Paper FrB16.1 | |
>Ancillary Services Provision Via Aggregation: Joint Power Flexibility Assessment and Disaggregation Policy Design |
|
Zamudio, Daniel | Politecnico Di Milano |
Falsone, Alessandro | Politecnico Di Milano |
Bianchi, Federico | Ricerca Sul Settore Energetico, RSE SpA |
Prandini, Maria | Politecnico Di Milano |
Keywords: Emerging control applications, Energy systems, Optimization
Abstract: We address the problem of assessing the power flexibility that a pool of prosumers equipped with a generalized storage device can offer to the electrical grid as an ancillary service for balancing power demand and generation. A key feature of the proposed approach is that the disaggregation policy is computed jointly with the aggregate flexibility set, and it is hence readily available for the pool to supply any (feasible) power profile request from the grid. Each prosumer is assumed to provide a contribution which is an affine function of the aggregated power profile. The coefficients of the affine policies are designed by solving a distributed optimization program where the volume of the aggregate flexibility set is maximized while satisfying the power and energy constraints of each storage device and additional constraints involving multiple (possibly all) devices. Simulation results show the superiority of the proposed approach with respect to a state-of-the-art method that inspired our work.
|
|
13:50-14:10, Paper FrB16.2 | |
>Feedback-Control Based Hierarchical Multi-Constraint Ad Campaign Optimization |
|
Karlsson, Niklas | Amazon |
Keywords: Emerging control applications, Hierarchical control, Optimization algorithms
Abstract: Online advertising is typically implemented via real-time bidding, and advertising campaigns are then defined as extremely high-dimensional optimization problems. Advertisers often define a campaign by an order consisting of multiple lines. Campaign delivery constraints may be imposed on the order as a whole and on each ad line. E.g., there may be budget and cost per click constraints on the order and on each line individually. Furthermore, the sum of line budgets may exceed the order budget, and the cost per click constraint on lines may differ. This leaves room for cross-line budget optimization; i.e., budget may be shifted across lines to maximize the advertising value without violating the constraints. This paper derives the optimal bidding mechanism for a large family of constrained optimization problems. It is shown how the optimal bidding strategy can be implemented as scalable non-cooperating agents on the order and the individual lines.
|
|
14:10-14:30, Paper FrB16.3 | |
>Entropy for Optimal Control on a Simplex with an Application to Behavioral Nudging |
|
Al Ahdab, Mohamad | Aalborg University |
Knudsen, Torben | Aalborg University, Denmark |
Stoustrup, Jakob | Aalborg University |
Leth, John | Aalborg University |
Keywords: Emerging control applications, Optimal control
Abstract: We study the utilization of the entropy function of inputs in solving two Optimal Control Problems (OCPs) with linear dynamics and inputs constrained to either a unit simplex, or a variable-sized simplex in which the size is also an input. By using the entropy function as part of the objective functional in the OCP, we are able to derive closed-form solutions for both cases. Additionally, we present an example of how the studied OCPs can be applied to choose between nudging techniques to encourage a specific behavior, such as adhering to medication, through the lens of behavioral momentum theory.
|
|
14:30-14:50, Paper FrB16.4 | |
>Power Purchase Agreements with Renewables: Optimal Timing and Design |
|
Gao, Zuguang | University of California, Irvine |
Sunar, Nur | University of North Carolina at Chapel Hill |
Birge, John | University of Chicago |
Keywords: Emerging control applications, Power systems, Optimal control
Abstract: In this paper, we design a power purchase agreement (PPA) where the firm agrees to make a certain transfer payment to the renewable generator, and the generator invests that payment to build new renewable energy facilities. The firm will then have access to all electricity generation from the new facilities for a long-term period. The firm may dynamically decide when to start the PPA on an ongoing basis, based on the evolving market conditions, and the transfer payment (amount of investment) is also specified by the firm. The firm's objective is to maximize its long-term discounted benefit (total savings) from signing the PPA. We mathematically formulate the firm's decision problem as an optimal stopping problem and provide analytical solutions. We also provide insights on how the firm's optimal investment capacity, expected savings, and the expected total new generation change with respect to different problem parameters.
|
|
14:50-15:10, Paper FrB16.5 | |
>An Error-Triggered Adaptive Model Reduction and Soil Moisture Estimation for Agro-Hydrological System |
|
Debnath, Sarupa | University of Alberta |
Sahoo, Soumya | University of Alberta |
Agyeman, Bernard | University of Alberta |
Yin, Xunyuan | Nanyang Technological University |
Liu, Jinfeng | University of Alberta |
Keywords: Emerging control applications, Reduced order modeling, Estimation
Abstract: Implementing a closed-loop irrigation system requires an accurate estimation of soil moisture given a limited number of sensors. However, the main challenge lies in the potential high dimensionality (10^{4}-10^{8}) of the agro-hydrological model used for water dynamics, which is modeled based on the nonlinear Richards equation. To address this challenge, we propose a state estimation method for large-scale agricultural fields. Our approach uses an error-triggered adaptive model reduction based on a trajectory-based clustering technique. An adaptive extended Kalman filter (EKF) is designed accordingly based on the adaptively reduced model. We apply our approach to an actual agricultural field and conduct extensive simulations to demonstrate its effectiveness and applicability.
|
|
15:10-15:30, Paper FrB16.6 | |
>Who Gets the Whip? How Supplier Diversification Influences Bullwhip Effect in a Supply Chain |
|
Burrows, Tyler | Brigham Young University |
Hamilton, Maxwell | Brigham Young University |
Grimsman, David | Brigham Young University |
Keywords: Modeling, Emerging control applications, Network analysis and control
Abstract: To navigate the evolving terrain of Supply Chains (SC), firms require new tools with broader applicability. Cur- rent research ignores the forest in favor of trees, with focal firms and serial networks assumed. This paper explicates a novel and scalable model for SC study at a broad level. We utilize the core of the model to observe the effect of structure and policy on demand disturbance in a SC as a whole. We find that complex structure alone does not effect change in disturbances; dynamic policy is necessary and sufficient for amplification. The model and simulations build to our main result: diversifying a firm’s supplier-base can amplify disturbances more quickly.
|
|
FrB17 |
Peony Junior 4511 |
Statistical Learning II |
Regular Session |
Chair: Qin, S. Joe | City University of Hong Kong |
Co-Chair: Farokhi, Farhad | The University of Melbourne |
|
13:30-13:50, Paper FrB17.1 | |
>Distributionally-Robust Optimization with Noisy Data for Discrete Uncertainties Using Total Variation Distance |
|
Farokhi, Farhad | The University of Melbourne |
Keywords: Statistical learning, Optimization, Uncertain systems
Abstract: Stochastic programs, where uncertainty distribution must be inferred from noisy data samples, are considered. They are approximated with distributionally-robust optimizations that minimize the worst-case expected cost over ambiguity sets, i.e., sets of distributions that are sufficiently compatible with observed data. The ambiguity sets capture probability distributions whose convolution with the noise distribution is within a ball centered at the empirical noisy distribution of data samples parameterized by total variation distance. Using the prescribed ambiguity set, the solutions of the distributionally-robust optimizations converge to the solutions of the original stochastic programs when the number of the data samples grow to infinity. Therefore, the proposed distributionally-robust optimization problems are asymptotically consistent. The distributionally-robust optimization problems can be cast as tractable optimization problems.
|
|
13:50-14:10, Paper FrB17.2 | |
>Robust Independence Tests with Finite Sample Guarantees for Synchronous Stochastic Linear Systems |
|
Tamás, Ambrus | SZTAKI |
Bálint, Dániel Ágoston | Independent Researcher |
Csáji, Balázs Cs. | SZTAKI |
Keywords: Statistical learning, Stochastic systems, Identification
Abstract: The paper introduces robust independence tests with non-asymptotically guaranteed significance levels for synchronous stochastic linear time-invariant systems, assuming that the observed outputs are simultaneous, which means that the systems are driven by jointly i.i.d. noises. Our method provides bounds for the type I error probabilities that are distribution-free, i.e., the innovations can have arbitrary distributions. The algorithm combines confidence region estimates with permutation tests and general dependence measures, such as the Hilbert–Schmidt independence criterion and the distance covariance, to detect any nonlinear dependence between the observed systems. We also prove the consistency of our hypothesis tests under mild assumptions and demonstrate the ideas through the example of autoregressive systems.
|
|
14:10-14:30, Paper FrB17.3 | |
>Towards Dynamic Causal Discovery with Rare Events: A Nonparametric Conditional Independence Test |
|
Chiu, Chih-Yuan | University of California, Berkeley |
Kulkarni, Kshitij | University of California, Berkeley |
Sastry, Shankar | Univ. of California at Berkeley |
Keywords: Statistical learning, Sampled-data control, Machine learning
Abstract: Causal phenomena associated with rare events occur across a wide range of engineering problems, such as risk-sensitive safety analysis, accident analysis and prevention, and extreme value theory. However, current methods for causal discovery are often unable to uncover causal links, between random variables in a dynamic setting, that manifest only when the variables first experience low-probability realizations. To address this issue, we introduce a novel statistical independence test on data collected from time-invariant dynamical systems in which rare but consequential events occur. In particular, we exploit the time-invariance of the underlying data to construct a superimposed dataset of the system state before rare events happen at different timesteps. We then design a conditional independence test on the reorganized data. We provide sample complexity bounds for the consistency of our method, and validate its performance across various simulated and real-world datasets, including incident data collected from the Caltrans Performance Measurement System (PeMS). Code containing the datasets and experiments is publicly available.
|
|
14:30-14:50, Paper FrB17.4 | |
>Distributionally Robust Stability of Payoff Allocations in Stochastic Coalitional Games |
|
Pantazis, George | TU Delft |
Franci, Barbara | Maastricht University |
Grammatico, Sergio | Delft University of Technology |
Margellos, Kostas | University of Oxford |
Keywords: Statistical learning, Uncertain systems, Game theory
Abstract: We consider multi-agent coalitional games with uncertainty in the coalitional values. We provide a novel methodology to study the stability of the grand coalition in the case where each coalition constructs ambiguity sets for the (possibly) unknown probability distribution of the uncertainty. As a less conservative solution concept compared to worst-case approaches for coalitional stability, we consider a stochastic version of the so-called core set, i.e., the expected value core. Unfortunately, without exact knowledge of the probability distribution, the evaluation of the expected value core is an extremely challenging task. Hence, we propose the concept of distributionaly robust (DR) core. Leveraging tools from DR optimization under the Wasserstein distance, we provide finite-sample guarantees that any allocation which lies in the DR core is also stable with respect to the true probability distribution and show the asymptotic consistency of the DR core. We dedicate the last section to the computational tractability of finding an allocation in the DR core.
|
|
14:50-15:10, Paper FrB17.5 | |
>Probabilistic Reduced-Dimensional Vector Autoregressive Modeling for Dynamics Prediction and Reconstruction with Oblique Projections |
|
Mo, Yanfang | City University of Hong Kong |
Yu, Jiaxin | CityU of Hong Kong |
Qin, S. Joe | Lingnan University |
Keywords: Process Control, Estimation, Statistical learning
Abstract: In this paper, we propose a probabilistic reduced-dimensional vector autoregressive (PredVAR) model with oblique projections. This model partitions the measurement space into a dynamic subspace and a static subspace that do not need to be orthogonal. The partition allows us to extract dynamic latent variables (DLVs) from high-dimensional data with maximized predictability. We develop an alternating iterative PredVAR algorithm using expectation maximization (EM) that exploits the interaction between updating the latent VAR dynamics and estimating the oblique projection. In addition, the noise covariance matrices are estimated as a natural outcome of the EM method. A simulation case study of the nonlinear Lorenz oscillation system illustrates the advantages of the proposed approach over two alternatives.
|
|
15:10-15:30, Paper FrB17.6 | |
>SIS Epidemic Propagation under Strategic Non-Myopic Protection: A Dynamic Population Game Approach |
|
Maitra, Urmee | Indian Institute of Technology, Kharagpur |
Hota, Ashish Ranjan | Indian Institute of Technology (IIT), Kharagpur |
Srivastava, Vaibhav | Michigan State University |
Keywords: Game theory, Stochastic systems
Abstract: We consider a dynamic game setting in which a large population of strategic individuals decides whether to adopt protective measures to protect themselves against an infectious disease, specifically the susceptible-infected-susceptible (SIS) epidemic. Protection is costly and partially effective, and adopting protection reduces the probability of becoming infected for susceptible individuals and the probability of transmitting the infection for infected individuals. In a departure from most prior works that assume the decision-makers to be myopic, we model individuals who choose their actions to maximize the infinite horizon discounted expected reward. We define the notion of best response and stationary Nash equilibrium in this class of games, and completely characterize the equilibrium policy and stationary state distribution for different parameter regimes. Numerical results illustrate the evolution and convergence of the infected proportion and the policy of protection adoption to the equilibrium.
|
|
FrB18 |
Peony Junior 4412 |
Stability of Nonlinear Systems IV |
Regular Session |
Chair: Martins, Nuno C. | University of Maryland |
Co-Chair: Murguia, Carlos | Eindhoven University of Technology |
|
13:30-13:50, Paper FrB18.1 | |
>A Submodular Energy Function Approach to Controlled Islanding with Provable Stability |
|
Cheng, Shiyu | Washington University in St. Louis |
Niu, Luyao | University of Washington |
Clark, Andrew | Washington University in St. Louis |
Poovendran, Radha | University of Washington |
Keywords: Stability of nonlinear systems, Optimization, Control of networks
Abstract: Cascading failures occur when failures of one or more nodes in a network lead to failures in neighboring nodes that propagate through the remainder of the network. One approach to mitigate cascading failures is through controlled islanding, in which a subset of edges is deliberately removed in order to partition the network into disjoint and stable islands. In this paper, we propose a submodular optimization algorithm for selecting edges to remove in order to create islands with provable stability. In contrast to existing approaches that optimize over stability-related metrics such as network coherence, our approach maps standard Lyapunov stability conditions to the objective function of an optimization problem. We prove that this optimization problem is equivalent to minimizing a supermodular function subject to a matroid basis constraint. We propose a local search algorithm for selecting the islands with provable optimality bounds, and discuss special cases including signed linear consensus and nonlinear synchronization dynamics. We simulate our approach using linear consensus dynamics with negative edges and find that our proposed algorithms partition the network into a stable island and an unstable island.
|
|
13:50-14:10, Paper FrB18.2 | |
>Homogeneous Finite/Fixed-Time Stabilization with Quantization |
|
Zhou, Yu | INRIA |
Polyakov, Andrey | Inria, Univ. Lille |
Zheng, Gang | INRIA |
Ping, Xubin | Xidian University |
Keywords: Stability of nonlinear systems, Quantized systems, Control over communications
Abstract: This paper investigates the stability of a homogeneous control system that uses quantized states. A sufficient condition for globally asymptotic (finite/nearly fixed-time) stability is derived. The stability under both uniform and logarithmic quantizers is investigated. It is demonstrated that a homogeneous feedback stabilization system with a uniform quantizer can achieve only practical stability. However, in the case of a logarithmic quantizer, the system can achieve global (finite-time, nearly fixed-time, exponential) stability, provided that the quantization density is sufficiently high. Additionally, homogeneous stabilizer design for a linear plant with quantized measurements is presented. Theoretical results are supported by numerical simulations.
|
|
14:10-14:30, Paper FrB18.3 | |
>Secondary Controller Design for the Safety of Nonlinear Systems Via Sum-Of-Squares Programming |
|
Lin, Yankai | Eindhoven University of Tecnology |
Chong, Michelle | Eindhoven University of Technology |
Murguia, Carlos | Eindhoven University of Technology |
Keywords: Stability of nonlinear systems, Resilient Control Systems, Numerical algorithms
Abstract: We consider the problem of ensuring the safety of nonlinear control systems under adversarial signals. Using Lyapunov-based reachability analysis, we first give sufficient conditions to assess safety, i.e., to guarantee that the states of the control system, when starting from a given initial set, always remain in a prescribed safe set. We consider polynomial systems with semi-algebraic safe sets. Using the S-procedure for polynomial functions, safety conditions can be formulated as a Sum-Of-Squares (SOS) programme, which can be solved efficiently. When safety cannot be guaranteed, we provide tools via SOS to synthesize polynomial controllers that enforce safety of the closed-loop system. The theoretical results are illustrated through numerical simulations.
|
|
14:30-14:50, Paper FrB18.4 | |
>Do 0-GAS-Guaranteeing Impulse Sequences Preserve ISS or iISS Properties? Not Always |
|
Russo, Antonio | Università Degli Studi Della Campania Luigi Vanvitelli |
Liu, Shenyu | Beijing Institute of Technology |
Keywords: Stability of hybrid systems, Lyapunov methods, Stability of nonlinear systems
Abstract: Based on the recent work on determination of classes of impulse/switching signals, uniformly over which a switched or impulsive system is input-to-state stable (ISS) or integral input-to-state stable (iISS), it is conjectured that for a switched system with all ISS or iISS subsystems, as long as the impulse/switching signal makes the system 0-input globally asymptotically stable (0-GAS), then it also ensures ISS and iISS, respectively. This work disproves this conjecture by showing examples where the impulse sequence amplifies the input, causing 0-GAS impulsive system to lose the ISS or iISS properties. As a compensation, we provide sufficient conditions on the impulse sequences which guarantee ISS or iISS. It turns out that these conditions are strictly stronger than those ensuring 0-GAS; the differences between them are in fact necessary conditions for the impulsive system to have the asymptotic gain (AG) property or uniformly bounded energy bounded state (UBEBS) property.
|
|
14:50-15:10, Paper FrB18.5 | |
>Counter-Adversarial Learning with Inverse Unscented Kalman Filter |
|
Singh, Himali | Indian Institute of Technology Delhi |
Mishra, Kumar Vijay | United States Army Research Laboratory |
Chattopadhyay, Arpan | Indian Institute of Technology, Delhi |
Keywords: Kalman filtering, Stability of nonlinear systems, Agents-based systems
Abstract: In counter-adversarial systems, to infer the strategy of an intelligent adversarial agent, the defender agent needs to cognitively sense the information that the adversary has gathered about the latter. Prior works on the problem employ linear Gaussian state-space models and solve this inverse cognition problem by designing inverse stochastic filters. However, in practice, counter-adversarial systems are generally highly nonlinear. In this paper, we address this scenario by formulating inverse cognition as a nonlinear Gaussian state-space model, wherein the adversary employs an unscented Kalman filter (UKF) to estimate the defender's state with reduced linearization errors. To estimate the adversary's estimate of the defender, we propose and develop an inverse UKF (IUKF) system. We then derive theoretical guarantees for the stochastic stability of IUKF in the mean-squared boundedness sense. Numerical experiments for multiple practical applications show that the estimation error of IUKF converges and closely follows the recursive Cramér-Rao lower bound.
|
|
15:10-15:30, Paper FrB18.6 | |
>Epidemic Population Games for Policy Design: Two Populations with Viral Reservoir Case Study (I) |
|
Certorio, Jair | University of Maryland |
La, Richard J. | University of Maryland, College Park |
Martins, Nuno C. | University of Maryland |
Keywords: Compartmental and Positive systems, Game theory, Stability of nonlinear systems
Abstract: We extend to two populations a recently proposed system theoretic framework for studying an epidemic influenced by the strategic behavior of a single population's agents. Our framework couples the well-known susceptible-infected-susceptible (SIS) epidemic model with a population game that captures the strategic interactions among the agents of two large populations. This framework can also be employed to study a situation where a population of nonstrategic agents (such as animals) serves as a disease reservoir. Equipped with the framework, we investigate the problem of designing a suitable control policy that assigns dynamic payoffs to incentivize the agents to adopt costlier and more effective mitigating strategies subject to a long-term budget constraint. We formulate a non-convex constrained optimization program for minimizing the disease transmission rate at an endemic equilibrium, and explain how to obtain an approximate solution efficiently. A solution to the optimization problem is an aggregate strategy distribution for the population game which minimizes the basic reproduction number at the corresponding endemic equilibrium, thus minimizing the transmission of the disease. We then propose a dynamic payoff mechanism and use a Lyapunov function to prove the convergence of i) the strategy distribution, ii) infection level, and iii) the dynamic payoff. Such that the strategy choices of the population converge to an (approximate) solution to the optimization problem, leading the level of infected to converge to the endemic equilibrium associated with the solution of the optimization.
|
|
FrB19 |
Peony Junior 4411 |
Filtering |
Regular Session |
Chair: Mahony, Robert | Australian National University, |
Co-Chair: Tanwani, Aneel | Laas -- Cnrs |
|
13:30-13:50, Paper FrB19.1 | |
>Sequential Learning from Noisy Data: Data-Assimilation Meets the Echo-State Network |
|
Goswami, Debdipta | Ohio State University |
Keywords: Filtering, Neural networks, Kalman filtering
Abstract: This paper explores the problem of training a recurrent neural network from noisy data. While neural network based dynamic predictors perform well with noise-free training data, prediction with noisy inputs during training phase poses a significant challenge. Here a sequential training algorithm is developed for an echo-state network (ESN) by incorporating noisy observations using an ensemble Kalman filter. The resultant Kalman-trained echo-state network (KalT-ESN) outperforms the traditionally trained ESN with least square algorithm while still being computationally cheap. The proposed method is demonstrated on noisy observations from three systems: two synthetic datasets from chaotic dynamical systems and a set of real-time traffic data.
|
|
13:50-14:10, Paper FrB19.2 | |
>H_infty Filter Based Functional Observers for Descriptor Systems |
|
Tunga, Pabitra Kumar | Indian Institute of Technology Patna |
Tomar, Nutan Kumar | Indian Institute of Technology Patna |
Keywords: Filtering, Observers for Linear systems, Differential-algebraic systems
Abstract: This paper considers the H_infty observers design problem for linear time-invariant descriptor systems. A sufficient condition is established for functional observers of order equal to the dimension of the vector to be estimated. This sufficient condition is milder than the other existing conditions in the literature. Furthermore, the observers are of the state space form, and the parameter matrices' existence is proved via elementary matrix theory. It is shown that the observer parameter matrices exist if a matrix equation is solvable. The solution of this matrix equation is not unique, and this non-uniqueness is utilized to meet other specifications of the observer via the solution theory of linear matrix inequalities (LMIs). The theoretical findings are illustrated by designing a functional observer for an electric circuit.
|
|
14:10-14:30, Paper FrB19.3 | |
>A Note on the Extended Kalman Filter on a Manifold |
|
Ge, Yixiao | Australian National University |
van Goor, Pieter | Australian National University |
Mahony, Robert | Australian National University, |
Keywords: Filtering, Observers for nonlinear systems, Algebraic/geometric methods
Abstract: The kinematics of many control systems, especially in the robotics field, naturally live on smooth manifolds. Most classical state-estimation algorithms, including the extended Kalman filter, are posed on Euclidean space. Although any filter algorithm can be adapted to a manifold setting by implementing it in local coordinates and ignoring the geometric structure, it has always been clear that there would be advantages in taking the geometric structure into consideration in developing the algorithm. In this paper, we argue that the minimum geometric structure required to adapt the extended Kalman filter to a manifold is that of an affine connection. With this structure, we show that a naive coordinate implementation of the EKF fails to account for geometry of the manifold in the update step and in the reset step. We provide geometric modifications to the classical EKF based on parallel transport of the measurement covariance (for the update) and a-posteriori state covariance (for the reset) that address these limitations. Preliminary results for attitude estimation with two directional measurements demonstrate that the proposed modifications significantly improve the transient behavior of the filter.
|
|
14:30-14:50, Paper FrB19.4 | |
>Transport Inspired Particle Filters with Poisson-Sampled Observations in Gaussian Setting |
|
Yufereva, Olga | LAAS CNRS |
Tanwani, Aneel | Laas -- Cnrs |
Keywords: Filtering, Sampled-data control, Randomized algorithms
Abstract: Motivated by the need for developing computationally efficient solutions to filtering problem with limited information, this article develops particle filtering algorithms for continuous-time stochastic processes with time-sampled observation process. The state process is modeled by a continuous-time linear stochastic differential equation driven by Wiener process, and the observation process is a linear mapping of the state with additive Gaussian noise. For practical reasons, we assume that the observations are time-sampled and the underlying sampling process is a Poisson counter. With the aim of developing particle filters for this system, we first propose a mean-field type process which is an observation-driven stochastic differential equation such that the conditional distribution of this process given the observations coincides with the optimal filtering distribution. This model is then used to simulate a collection of particles which are driven only by the sample mean and sample covariance, without simulating the differential equation for the covariance matrix. It is shown that the dynamics of the sample mean and the sample covariance coincide with the optimal ones. An academic example is included for illustration.
|
|
14:50-15:10, Paper FrB19.5 | |
>Fusion of Distance Measurements between Agents with Unknown Correlations |
|
Cros, Colin | Université Grenoble Alpes |
Amblard, Pierre-Olivier | CNRS |
Prieur, Christophe | CNRS |
Da Rocha, Jean-François | Telespazio FRANCE |
Keywords: Filtering, Sensor networks, Cooperative control
Abstract: Cooperative localization is a promising solution to improve the accuracy and overcome the shortcomings of GNSS. Cooperation is often achieved by measuring the distance between users. To optimally integrate a distance measurement between two users into a navigation filter, the correlation between the errors of their estimates must be known. Unfortunately, in large scale networks the agents cannot compute these correlations and must use consistent filters. A consistent filter provides an upper bound on the covariance of the error of the estimator taking into account all the possible correlations. In this paper, a consistent linear filter for integrating a distance measurement is derived using Split Covariance Intersection. Its analysis shows that a distance measurement between two agents can only benefit one of them, i.e., only one of the two can use the distance measurement to improve its estimator. Furthermore, in some cases, none can. A necessary condition for an agent to benefit from the measurement is given for a general class of objective functions. When the objective function is the trace or the determinant, necessary and sufficient conditions are given.
|
|
15:10-15:30, Paper FrB19.6 | |
>Metrics for Bayesian Optimal Experiment Design under Model Misspecifications |
|
Catanach, Tommie | Sandia National Laboratories |
Das, Niladri | Sandia National Laboratories |
Keywords: Kalman filtering, Filtering, Uncertain systems
Abstract: The conventional approach to Bayesian decision-theoretic experiment design involves searching over possible experiments to select a design that maximizes the expected value of a specified utility function. The expectation is over the joint distribution of all unknown variables implied by the statistical model that will be used to analyze the collected data. Utility functions define experiments’ objectives; a common utility function is information gain. This article introduces an expanded framework for experimental design, where we go beyond the traditional Expected Information Gain criteria. We introduce Expected General Information Gain which measures robustness to the model discrepancy, and Expected Discriminatory Information to quantify how well an experiment can detect model discrepancy. The functionality of the framework is showcased through its application to a scenario involving a linearized spring mass damper system and an F-16 model where the model discrepancy is taken into account while doing Bayesian optimal experiment design.
|
|
FrB20 |
Orchid Junior 4312 |
Modelling and Control II |
Regular Session |
Chair: Palopoli, Luigi | University of Trento |
Co-Chair: Tebaldi, Davide | University of Modena and Reggio Emilia |
|
13:30-13:50, Paper FrB20.1 | |
>Tube-Based Control Barrier Function with Integral Quadratic Constraints for Unknown Input Delay |
|
Quan, Yingshuai | Hanyang University |
Kim, Jin Sung | Hanyang University |
Lee, Seung Hi | Hongik University |
Chung, Chung Choo | Hanyang University |
Keywords: Robust control, Constrained control, Optimal control
Abstract: This paper proposes a Control Barrier Function (CBF)-based controller design to achieve safety for systems subjecting to unknown input delay and additive disturbance. Integral quadratic constraints characterizing the input-output behavior of the unmodeled dynamics caused by the unknown input delay are used to generate a bound of the error between the nominal model and the true uncertain system. The bound is incorporated into a tube-based CBF formulation to ensure robust system safety. The proposed method guarantees that the constraints are input affine, so the safe controller can be implemented by solving a quadratic programming problem in real-time. A simple example demonstrates the effectiveness of the tube-based CBF approach.
|
|
13:50-14:10, Paper FrB20.2 | |
>A Generalized Procedure to Model Complex Time-Varying Physical Systems |
|
Tebaldi, Davide | University of Modena and Reggio Emilia |
Zanasi, Roberto | University of Modena and Reggio Emilia |
Keywords: Modeling, Mechatronics, Time-varying systems
Abstract: This paper addresses the systematic modeling of complex physical systems involving constant and time-varying interactions of physical elements in different energetic domains. The proposed procedure provides two different dynamic models of the considered system: a full-order one and a reduced-order one, where the latter is obtained when some of the system dynamical elements are properly disregarded. The matrices and vectors of the two dynamic models are automatically computed following the proposed rules and algorithms, thus reducing the chances of making computation mistakes. The proposed procedure is applied to two different case studies: an hydraulic continuous variable transmission for powertrain dynamics and a crank-connecting rod system in the mechatronic field.
|
|
14:10-14:30, Paper FrB20.3 | |
>Exploiting Invariance Properties to Certify Always and Eventually Signal Temporal Logic Operators for Hybrid Dynamical Systems |
|
Han, Hyejin | University of California, Santa Cruz |
Sanfelice, Ricardo G. | University of California at Santa Cruz |
Keywords: Hybrid systems, Lyapunov methods, Model Validation
Abstract: In this paper, semantics and characterizations of signal temporal logic formulas for hybrid dynamical systems are presented. Hybrid dynamical systems are given in terms of constrained differential and difference inclusions, which, respectively, capture the continuous evolution and the instan- taneous events exhibited by solutions. For such systems, the always and eventually operator of signal temporal logic are studied and characterizations in terms of dynamical properties of hybrid systems are presented – in particular, using invariance and finite-time attractivity properties. Sufficient conditions that guarantee the satisfaction of a signal temporal logic formula for a given system through the satisfaction of an untimed formula for an appropriately defined new system are introduced. Specif- ically, it is shown that satisfying an (untimed) temporal logic formula involving until operators suffices to certify always and eventually signal temporal logic formulas for hybrid systems.
|
|
14:30-14:50, Paper FrB20.4 | |
>Strictly Uniform Exponential Decay of the Mixed-FEM Discretization for the Wave Equation with Boundary Dissipation |
|
Del Rey Fernández, David C. | University of Waterloo |
Mora, Luis A. | University of Waterloo |
Morris, Kirsten | University of Waterloo |
Keywords: Distributed parameter systems, Stability of linear systems, Linear systems
Abstract: Uniform preservation of stability in approximations of wave equations is a long-standing issue. In this paper, a one-dimensional wave equation with a partially reflective boundary is approximated using a first-order mixed finite element method. The multiplier method is used to prove that the approximated systems are exponentially stable with a decay rate independent of the mesh size. Upper bounds on the exponential decay are obtained in terms of the physical parameters.
|
|
14:50-15:10, Paper FrB20.5 | |
>Experimental Results for a Pressure Reducer Control with a Modular Actuator |
|
Ariba, Yassine | INSA |
Gouaisbaut, Frederic | University of Toulouse, LAAS CNRS |
Deschaux, Flavien | COMAT |
Dugué, François | CSTM |
Roux, François | CSTM |
Keywords: Mechatronics, Lyapunov methods, Control applications
Abstract: This paper addresses the control of a pressure regulator which reduces the pressure from an upstream chamber to a desired lower pressure in a downstream one. Most results in the literature, either neglect the actuator dynamic embedded in the reducer, or develop a specific design dedicated to their system. In this study, we propose to take into account this inner dynamic with a control system designed independently. The objective is to enable a modular architecture. It also justifies classical cascade control approach. A modeling work of the physical system combined with some practical assumptions provides a simple linear model. An output feedback control is designed to ensure stability, performance requirements and to cope with a saturation nonlinearity. This phenomenon is necessarily present due to physical limitations of the fluid flow rate in the actuator. Robust analysis approach and sector condition are used to address this feature as well as to take into account the dynamic of the independent controlled actuator with reduced assumptions on this subsystem. Stability condition of the overall system is expressed with LMI tests. Simulation and experimental tests show the validity of the proposed methodology.
|
|
15:10-15:30, Paper FrB20.6 | |
>Notch Filter Design with Stability Guarantees for Mechanical Resonance Suppression in SISO LTI Two-Mass Drive Systems |
|
Sonzogni, Giulia | Università Degli Studi Di Bergamo |
Mazzoleni, Mirko | University of Bergamo |
Polver, Marco | Università Degli Studi Di Bergamo |
Ferramosca, Antonio | Univeristy of Bergamo |
Previdi, Fabio | Università Degli Studi Di Bergamo |
Keywords: Mechatronics, Control applications, Simulation
Abstract: Although the suppression of mechanical resonances for drive and positioning systems is a well-understood problem in the literature, its importance is still actual as technological developments push towards an increase in performance requirements. In this paper, the design of a notch filter is investigated with the aim of suppressing a single resonant frequency in SISO LTI two-mass drive systems. In the cases where the notch filter is located inside an existing control loop, as assumed in this work, it must not compromise the closed-loop stability of the system, while assuring desired control bandwidth and stability margins. Given a fixed known resonant frequency to suppress, an automatic algorithm is proposed to tune the notch filter parameters to guarantee specified control requirements and stability of the closed-loop system, so as to avoid, whenever possible, the reconfiguration of a preexisting controller.
|
|
FrB21 |
Orchid Junior 4311 |
Transportation Networks |
Regular Session |
Chair: Chen, Minghua | City University of Hong Kong |
Co-Chair: Frasca, Paolo | CNRS, GIPSA-Lab, Univ. Grenoble Alpes |
|
13:30-13:50, Paper FrB21.1 | |
>Arc-Based Traffic Assignment: Equilibrium Characterization and Learning |
|
Chiu, Chih-Yuan | University of California, Berkeley |
Maheshwari, Chinmay | University of California Berkeley |
Su, Pan-Yang | University of California, Berkeley |
Sastry, Shankar | Univ. of California at Berkeley |
Keywords: Transportation networks, Game theory, Adaptive systems
Abstract: Arc-based traffic assignment models (TAMs) are a popular framework for modeling traffic network congestion generated by self-interested travelers who sequentially select arcs based on perceived arc latencies. However, existing arc-based TAMs either assign travelers to cyclic paths, or do not extend to networks with bi-directional edges between nodes. To overcome these difficulties, we propose a new modeling framework for stochastic arc-based TAMs. Given a traffic network with bidirectional edges, we replicate its arcs and nodes to construct a directed acyclic graph (DAG), which we call the Condensed DAG (CoDAG) representation of the original network. Self-interested travelers are then modeled as sequentially selecting arcs on the CoDAG. We show that the associated equilibrium flow, which we call the Condensed DAG equilibrium, exists, is unique, and can be characterized as the solution to a strictly convex optimization problem. Moreover, we propose an adaptive learning rule which ensures that self-interested travelers, who repeatedly update their arc selection rules, will converge to a neighborhood of the Condensed DAG equilibrium. To the best of our knowledge, this is the first learning scheme that provably converges to an arc-based traffic equilibrium. Finally, we present numerical results on simulated traffic networks that corroborate our theoretical results.
|
|
13:50-14:10, Paper FrB21.2 | |
>Distributed Leader-Followers Constrained Platooning Control of Linear Homogeneous Vehicles |
|
Gaagai, Ramzi | Helmut-Schmidt-Universität - Universität Der Bundeswehr Hamburg |
Giaccagli, Mattia | Tel Aviv University |
Horn, Joachim | Helmut-Schmidt-University / University of the Federal Armed Forc |
Keywords: Transportation networks, Networked control systems, Linear systems
Abstract: This paper presents a feedback-distributed controller that guarantees exponential synchronization of a vehicle platoon described by linear dynamics. To achieve desired intervehicle spacing between two vehicles and to improve platoon cohesiveness, a leader-based bidirectional communication scheme is employed. To take into account the constraints of the system and to avoid collision between vehicles, safety features are implemented using control barrier functions via linear quadratic programming. String stability properties of the platoon are analyzed, where we show via simulations that the proposed design allows considering a gap-spacing policy for inter-vehicle distance with zero headway. To conclude, the effectiveness of the proposed controller is verified in a simulation study.
|
|
14:10-14:30, Paper FrB21.3 | |
>Stability Analysis for a Platoon of Vehicles with Reaction-Time Delay |
|
Mousavi, Shima Sadat | ETH Zurich |
Bahrami, Somayeh | Razi University |
Kouvelas, Anastasios | ETH Zurich |
Keywords: Transportation networks, Nonlinear systems, Delay systems
Abstract: This paper explores collective dynamics in a group of multiple homogeneous vehicles on a ring-road using the Optimal Velocity Model (OVM). To account for real-world traffic scenarios, driver reaction time is incorporated as a time-delay system. Analyzing stability, we initially focus on the equilibrium motion regime, where vehicles maintain uniform speed and spacing. This is achieved through linearization and examining the impact of model parameters. Subsequently, we extend our analysis to the full nonlinear model, determining the equilibrium's region of attraction by solving Linear Matrix Inequalities (LMIs) and estimating ellipsoids.
|
|
14:30-14:50, Paper FrB21.4 | |
>Minimizing Carbon Footprint for Timely E-Truck Transportation: Hardness and Approximation Algorithm (I) |
|
Su, Junyan | City University of Hong Kong |
Lin, Qiulin | City University of Hong Kong |
Chen, Minghua | City University of Hong Kong |
Zeng, Haibo | Virginia Tech |
Keywords: Transportation networks
Abstract: Carbon footprint optimization (CFO) is important for sustainable heavy-duty e-truck transportation. We consider the CFO problem for timely transportation of e-trucks, where the truck travels from an origin to a destination across a national highway network subject to a deadline. The goal is to minimize the carbon footprint by orchestrating path planning, speed planning, and intermediary charging planning. We first show that it is NP-hard even just to find a feasible CFO solution. We then develop a (1+eps F, 1+eps b) bi-criteria approximation algorithm that achieves a carbon footprint within a ratio of 1+eps F to the minimum with no deadline violation and at most a ratio of 1+eps b battery capacity violation (for any positive eps F and eps b). Its time complexity is polynomial in the size of the highway network, 1/eps F, and 1/eps b. Such algorithmic results are among the best possible unless P=NP. Simulation results based on real-world traces show that our scheme reduces up to 11% carbon footprint as compared to baseline alternatives considering only energy consumption but not carbon footprint.
|
|
14:50-15:10, Paper FrB21.5 | |
>Impact on Traffic of Delayed Information in Navigation Systems |
|
Toso, Tommaso | Université Grenoble Alpes, CNRS, Inria, Grenoble INP, GIPSA-Lab |
Kibangou, Alain | Univ. Grenoble Alpes |
Frasca, Paolo | CNRS, GIPSA-Lab, Univ. Grenoble Alpes |
Keywords: Transportation networks, Delay systems
Abstract: Nowadays many car drivers resort to navigation apps to decide which route to take. To be efficient, these applications increasingly use real-time data rather than historical data. However, delay is unavoidable since data collection, communication, and processing are necessary before their usage in the App. For this purpose, we introduce a macroscopic dynamic traffic assignment model to describe the behaviour of drivers in choosing which route to follow to reach their destination. We assume that a part of the drivers follows the directions of a navigation App, whose directions are based on delayed traffic data. Through the stability analysis of the model, we show and quantify the excessive level of delay in traffic data that can be detrimental to the efficiency of the network by being responsible for the appearance of oscillating trajectories and unsatisfied demand.
|
|
15:10-15:30, Paper FrB21.6 | |
>Assessing the Impact of Non-Compliant Users Response to System-Optimal Dynamic Traffic Assignment (I) |
|
Siri, Enrico | Inria Sophia, Université Côte D'Azur |
Goatin, Paola | Inria |
Keywords: Transportation networks, Optimal control, Modeling
Abstract: In the present work, we address a pseudo - System Optimum Dynamic Traffic Assignment optimization problem on road networks relying on trajectory control over a portion of the flows and limited knowledge on user response. The fractions of controlled flow moving between each origin-destination couple are defined as compliant, while the remaining portions, consisting of users free to make their own individual choices, are defined as non-compliant. The objective is to globally improve the state of the network by controlling a varying sub-set of compliant traffic flows. A Godunov discretization of the Lighthill-Williams-Richards model coupled with a triangular fundamental diagram is employed as the flow dynamics model. At junctions, a multi-class solver is applied which requires a class-density-weighted aggregate distribution matrix and incoming links priorities. On one hand, the selfish response of non-compliant users to changing traffic conditions is computed at each time step by updating the class related turn ratios accordingly to a discrete-choice multinomial Logit model to represent users imperfect information. On the other hand, the control action is actuated by varying the flow rates over a pre-computed set of routes while the coupled optimization problem takes into account an a priori fixed distribution of users at the nodes. We show how the effectiveness of the resulting finite horizon optimal control problem degrades by not considering the dynamic response of non-compliant users and how it varies according to the fraction of compliant ones.
|
|
FrB22 |
Orchid Junior 4212 |
Markov Processes |
Regular Session |
Chair: Meyn, Sean P. | Univ. of Florida |
Co-Chair: Mahajan, Aditya | McGill University |
|
13:30-13:50, Paper FrB22.1 | |
>Optimizing Sensor Allocation against Attackers with Uncertain Intentions: A Worst-Case Regret Minimization Approach |
|
Ma, Haoxiang | University of Florida |
Han, Shuo | University of Illinois Chicago |
Kamhoua, Charles | U.S. Army Research Laboratory |
Fu, Jie | University of Florida |
Keywords: Markov processes, Game theory, Optimization
Abstract: This paper focuses on the optimal allocation of multi-stage attacks with the uncertainty in attacker's intention. We model the attack planning problem using a Markov decision process and characterize the uncertainty in the attacker's intention using a finite set of reward functions---each reward represents a type of attacker. Based on this modeling, we employ the paradigm of the worst-case absolute regret minimization from robust game theory and develop mixed-integer linear program (MILP) formulations for solving the worst-case regret minimizing sensor allocation strategies for two classes of attack-defend interactions: one where the defender and attacker engage in a zero-sum game and another where they engage in a non-zero-sum game. We demonstrate the effectiveness of our algorithm using a stochastic gridworld example.
|
|
13:50-14:10, Paper FrB22.2 | |
>Distributed TD(0) with Almost No Communication |
|
Liu, Rui | Boston University |
Olshevsky, Alexander | Boston University |
Keywords: Markov processes, Machine learning, Cooperative control
Abstract: We provide a new non-asymptotic analysis of distributed temporal difference learning with linear function approximation. Our approach relies on ``one-shot averaging,'' where N agents run identical local copies of the TD(0) method and average the outcomes only once at the very end. We demonstrate a version of the linear time speedup phenomenon, where the convergence time of the distributed process is a factor of N faster than the convergence time of TD(0). This is the first result proving benefits from parallelism for temporal difference methods.
|
|
14:10-14:30, Paper FrB22.3 | |
>The Curse of Memory in Stochastic Approximation |
|
Lauand, Caio Kalil | University of Florida |
Meyn, Sean P. | Univ. of Florida |
Keywords: Randomized algorithms, Stochastic optimal control, Markov processes
Abstract: Theory and application of stochastic approximation (SA) has grown within the control systems community since the earliest days of adaptive control. This paper takes a new look at the topic, motivated by recent results establishing remarkable performance of SA with (sufficiently small) constant step-size alpha>0. If averaging is implemented to obtain the final parameter estimate, then the estimates are asymptotically unbiased with nearly optimal asymptotic covariance. These results have been obtained for random linear SA recursions with i.i.d. coefficients. This paper obtains very different conclusions in the more common case of geometrically ergodic Markovian disturbance: (i) The target bias is identified, even in the case of non-linear SA, and is in general non-zero. The remaining results are established for linear SA recursions: (ii) the bivariate parameter-disturbance process is geometrically ergodic in a topological sense; (iii) the representation for bias has a simpler form in this case, and cannot be expected to be zero if there is multiplicative noise; (iv) the asymptotic covariance of the averaged parameters is within O(alpha) of optimal. The error term is identified, and may be massive if mean dynamics are not well conditioned. The theory is illustrated with application to TD-learning.
|
|
14:30-14:50, Paper FrB22.4 | |
>Asymmetric Actor-Critic with Approximate Information State |
|
Sinha, Amit | McGill University |
Mahajan, Aditya | McGill University |
Keywords: Markov processes, Stochastic optimal control, Learning
Abstract: Reinforcement learning (RL) for partially observable Markov decision processes (POMDPs) is a challenging problem because decisions need to be made based on the entire history of observations and actions. However, in several scenarios, state information is available during the training phase. We are interested in exploiting the availability of this state information during the training phase to efficiently learn a history-based policy using RL. Specifically, we consider actor-critic algorithms, where the actor uses only the history information but the critic uses both history and state. Such algorithms are called asymmetric actor-critic, to highlight the fact that the actor and critic have asymmetric information. Motivated by the recent success of using representation losses in RL for POMDPs [1], we derive similar theoretical results for the asymmetric actor-critic case and evaluate the effectiveness of adding such auxiliary losses in experiments. In particular, we learn a history representation---called an approximate information state (AIS)---and bound the performance loss when acting using AIS.
|
|
14:50-15:10, Paper FrB22.5 | |
>Weighted-Norm Bounds on Model Approximation in MDPs with Unbounded Per-Step Cost |
|
Bozkurt, Berk | McGill University |
Mahajan, Aditya | McGill University |
Nayyar, Ashutosh | University of Southern California |
Ouyang, Yi | Preferred Networks |
Keywords: Markov processes, Stochastic optimal control, Stochastic systems
Abstract: We consider the problem of designing a control policy for an infinite-horizon discounted cost Markov Decision Process (MDP) mathcal{M} when we only have access to an approximate model hat{mathcal M}. If we design an optimal policy hat pi^star for the approximate model, how well does it perform when used in the true model mathcal M? We provide an answer to this question by bounding a weighted norm of the difference between the value function of hat pi^star when used in mathcal M and the optimal value function of mathcal M. The use of weighted norm allows us to obtain meaningful bounds for performance loss even when the per-step cost function is unbounded. This is in contrast to much of the prior literature which has largely focused only on the case of bounded per-step cost. We illustrate our results for two specific instances — a finite MDP model for an inventory control problem and the discounted linear quadratic regulator problem.
|
|
15:10-15:30, Paper FrB22.6 | |
>Optimal Markov Policies for Finite-Horizon Constrained MDPs with Combined Additive and Multiplicative Utilities |
|
M, Uday Kumar | Tata Consultancy Services Limited |
Bhat, Sanjay P. | Tata Consultancy Services Limited |
Veeraruna, Kavitha | IIT Bombay, India |
Hemachandra, Nandyala | Indian Institute of Technology Bombay |
Keywords: Optimization, Optimal control, Markov processes
Abstract: This paper considers the problem of optimizing a finite-horizon constrained Markov decision process (CMDP) where the objective and constraints are sums of additive and multiplicative utilities. To solve this, we construct another CMDP with only additive utilities whose optimal value over a restricted set of policies is equal to that of the original CMDP. Further, we provide a finite-dimensional bilinear program (BLP) whose value equals the CMDP value and whose solution provides the optimal policy. We also suggest an algorithm to solve the proposed BLP.
|
|
FrB23 |
Orchid Junior 4211 |
Formal Verification and Synthesis |
Regular Session |
Chair: Zhang, Zengjie | Eindhoven University of Technology |
Co-Chair: Pola, Giordano | University of L'Aquila |
|
13:30-13:50, Paper FrB23.1 | |
>Computing Controlled Invariant Sets of Nonlinear Control-Affine Systems |
|
Brown, Scott | University of California, San Diego |
Khajenejad, Mohammad | University of California, San Diego |
Yong, Sze Zheng | Northeastern University |
Martinez, Sonia | University of California at San Diego |
Keywords: Formal Verification/Synthesis, Nonlinear systems, Computational methods
Abstract: In this paper, we consider the computation of controlled invariant sets (CIS) of discrete-time nonlinear control-affine systems. We propose an iterative refinement procedure based on polytopic inclusion functions, which is able to inner-approximate the maximal controlled invariant set to within a guaranteed robustness margin. In particular, this procedure allows us to guarantee the invariance of the resulting near-maximal CIS while also computing sets of control inputs which enforce the invariance. Further, we propose an alternative version of this procedure which refines the CIS by computing backward reachable sets of individual components of set unions, rather than all at once. This reduces the total number of inclusion checking operations required for convergence,especially when compared with existing methods. Finally, we compare our methods to a sampling based approach and demonstrate the improved accuracy and faster convergence.
|
|
13:50-14:10, Paper FrB23.2 | |
>On Nash Equilibria for Decentralized Symbolic Control of Interconnected Finite State Systems |
|
Pola, Giordano | University of L'Aquila |
De Santis, Elena | University of L'Aquila |
Di Benedetto, Maria Domenica | University of L'Aquila |
Keywords: Formal Verification/Synthesis, Decentralized control, Game theory
Abstract: In this paper we consider a pair of interconnected nondeterministic and metric finite state systems and address a decentralized symbolic control problem where controllers are designed for enforcing local specifications expressed in terms of regular languages, up to a desired accuracy. The considered control architecture is decentralized, i.e. each controller can only communicate with the corresponding plant. Since plant systems are interconnected, the part of the specification that can be enforced on one system depends on the one on the other system. We show how this dependency can be nicely formalized in terms of equilibria and in particular, of Nash equilibria. When controlled plants are at a Nash equilibrium, deviation of each plant from its control strategy may correspond to a loss in terms of the part of specification enforced. Algorithms are proposed which converge, when an equilibrium exists, to Nash equilibria.
|
|
14:10-14:30, Paper FrB23.3 | |
>Exact and Cost-Effective Automated Transformation of Neural Network Controllers to Decision Tree Controllers |
|
Chang, Kevin | University of Southern California |
Dahlin, Nathan | University of Illinois at Urbana-Champaign |
Jain, Rahul | University of Southern California |
Nuzzo, Pierluigi | University of Southern California |
Keywords: Formal Verification/Synthesis, Hybrid systems, Machine learning
Abstract: Over the past decade, neural network (NN)-based controllers have demonstrated remarkable efficacy in a variety of decision-making tasks. However, their black-box nature and the risk of unexpected behaviors and surprising results pose a challenge to their deployment in real-world systems with strong guarantees of correctness and safety. We address these limitations by investigating the transformation of NN-based controllers into equivalent soft decision tree (SDT)-based controllers and its impact on verifiability. Differently from previous approaches, we focus on discrete-output NN controllers including rectified linear unit (ReLU) activation functions as well as argmax operations. We then devise an exact but cost-effective transformation algorithm, in that it can automatically prune redundant branches. We evaluate our approach using two benchmarks from the OpenAI Gym environment. Our results indicate that the SDT transformation can benefit formal verification, showing runtime improvements of up to 21x and 2x for MountainCar-v0 and CartPole-v1, respectively.
|
|
14:30-14:50, Paper FrB23.4 | |
>Model Predictive Control for Signal Temporal Logic Specifications with Time Interval Decomposition |
|
Yu, Xinyi | University of Southern California |
Wang, Chuwei | Shanghai Jiao Tong University |
Yuan, Dingran | Shanghai Jiao Tong University |
Li, Shaoyuan | Shanghai Jiao Tong University |
Yin, Xiang | Shanghai Jiao Tong University |
Keywords: Formal Verification/Synthesis, Hybrid systems, Predictive control for nonlinear systems
Abstract: In this paper, we investigate the problem of Model Predictive Control (MPC) of dynamic systems for high- level specifications described by Signal Temporal Logic (STL) formulae. Recent works show that MPC has the great potential in handling logical tasks in reactive environments. However, existing approaches suffer from the heavy computational bur- den, especially for tasks with large horizons. In this work, we propose a computationally more efficient MPC framework for STL tasks based on time interval decomposition. Specifically, we still use the standard shrink horizon MPC framework with Mixed Integer Linear Programming (MILP) techniques for open-loop optimization problems. However, instead of applying MPC directly for the entire task horizon, we decompose the STL formula into several sub-tasks with disjoint time horizons, and shrinking horizon MPC is applied for each short-horizon sub-task iteratively. To guarantee the satisfaction of the entire STL formula and to ensure the recursive feasibility of the iterative process, we introduce new terminal constraints to connect each sub-task. We show how these terminal constraints can be computed by an effective inner-approximation approach. The computational efficiency of our approach is illustrated by a case study.
|
|
14:50-15:10, Paper FrB23.5 | |
>Modularized Control Synthesis for Complex Signal Temporal Logic Specifications |
|
Zhang, Zengjie | Eindhoven University of Technology |
Haesaert, Sofie | Eindhoven University of Technology |
Keywords: Formal Verification/Synthesis, Optimization, Computational methods
Abstract: The control synthesis of a dynamic system subject to a signal temporal logic (STL) specification is commonly formulated as a mixed-integer linear/convex programming (MILP/MICP) problem. Solving such a problem is computationally expensive when the specification is long and complex. In this paper, we propose a framework to transform a long and complex specification into separate forms in time, to be more specific, the logical combination of a series of short and simple subformulas with non-overlapping timing intervals. In this way, one can easily modularize the synthesis of a long specification by solving its short subformulas, which improves the efficiency of the control problem. We first propose a syntactic timing separation form for a type of complex specifications based on a group of separation principles. Then, we further propose a complete specification split form with subformulas completely separated in time. Based on this, we develop a modularized synthesis algorithm that ensures the soundness of the solution to the original synthesis problem. The efficacy of the methods is validated with a robot monitoring case study in simulation. Our work is promising to promote the efficiency of control synthesis for systems with complicated specifications.
|
|
15:10-15:30, Paper FrB23.6 | |
>Optimal Path Planning with Opacity-Preserving Temporal Logic Specifications Using Bipartite Synthesizers (I) |
|
Zheng, Yiwei | Xiamen University |
Lai, Aiwen | Xiamen University |
Lan, Weiyao | Xiamen University |
Yu, Xiao | Xiamen University |
Keywords: Formal Verification/Synthesis, Discrete event systems, Robotics
Abstract: This paper investigates an optimal planning problem with the requirement of preventing high-level mission specifications from being revealed to the intruder. We assume that the behavior of the robotic system at some specific locations is partially observable, and the intruder is modeled as a passive observer for the observable behavior and the corresponding overall transition cost of the trajectories. We first use the transition system to model the robot system. Then, we say that the transition system is LTL-based opaque with respect to high-level mission specifications if the intruder cannot infer the exact behavior of the system via the observable sequence of the system. We design a synthesizer for the product automaton of the transition system and the Büchi automaton to find the evolutions of possible reachable states. Based on the synthesizer, the corresponding run can be synthesized in which the optimality, correctness, and opacity can be guaranteed.
|
|
FrB24 |
Orchid Main 4201AB |
Sliding-Mode Control |
Regular Session |
Chair: Ferrara, Antonella | University of Pavia |
Co-Chair: Kim, Yoonsoo | Gyeongsang National University |
|
13:30-13:50, Paper FrB24.1 | |
>Multivariable Disturbance Observer-Based Finite-Time Sliding Mode Attitude Control for Fixed-Wing UAVs under Matched and Mismatched Disturbances |
|
Nguyen, Ngo Phong | Ulsan National Institute of Science and Technology |
Oh, Hyondong | Ulsan National University of Science and Technology |
Moon, Jun | Hanyang University |
Kim, Yoonsoo | Gyeongsang National University |
Keywords: Variable-structure/sliding-mode control, Control applications
Abstract: In this letter, we propose a multivariable disturbance observer-based finite-time sliding mode attitude control (MDOB-FT-SM-AC) for fixed-wing UAVs in the presence of both matched and mismatched disturbances. Compared with existing sliding mode attitude controllers, the significant improvements of the proposed MDOB-FT-SM-AC are the multi- variable control structure, strong robustness, and high precision performance with continuous control input signal. In the proposed MDOB-FT-SM-AC, we first develop multivariable finite-time disturbance observers such that the precise estimation of both matched and mismatched disturbances is ensured. Next, a nonsingular terminal sliding manifold is designed such that the fixed-wing UAV is driven to track its desired attitude command in finite time. We finally present a multivariable super-twisting reaching law such that the finite-time convergence of the sliding variable and its derivative to zero is guaranteed. Attentive finite- time convergence analysis is derived based on the Lyapunov and homogeneity theories. Simulation results are given to illustrate the superiority of the proposed MDOB-FT-SM-AC.
|
|
13:50-14:10, Paper FrB24.2 | |
>Exact Differentiator with Lipschitz Continuous Output and Optimal Worst-Case Accuracy under Bounded Noise |
|
Aldana-López, Rodrigo | Universidad De Zaragoza |
Seeber, Richard | Graz University of Technology |
Haimovich, Hernan | CONICET and UNR |
Gomez-Gutierrez, David | Intel Labs |
Keywords: Variable-structure/sliding-mode control, Estimation, Time-varying systems
Abstract: The online differentiation of a signal contaminated with bounded noise is addressed. A differentiator is developed that generates a Lipschitz continuous output, is exact in the absence of noise, and provides the optimal worst-case accuracy among all possible exact differentiators when noise is present. This combination of features is not shared by any previously existing differentiator. Tuning of the developed differentiator is very simple, requiring only the knowledge of a bound for the second-order derivative of the signal. The approach consists in regularizing the possibly highly noisy output of a recently introduced linear adaptive robust exact differentiator and feeding it to a first-order sliding-mode filter designed to maintain optimal accuracy. The proposed regularization and filtering of this output allows trading the speed with which exactness is obtained for the feature of a Lipschitz continuous, hence less noisy, output. An illustrative example is provided to highlight the features of the developed differentiator.
|
|
14:10-14:30, Paper FrB24.3 | |
>A Passivity Based Integral Sliding Mode Controller for Mechanical Port-Hamiltonian Systems |
|
Baba, Takahiro | Kyoto University |
Fujimoto, Kenji | Kyoto University |
Maruta, Ichiro | Kyoto University |
Keywords: Variable-structure/sliding-mode control, Lyapunov methods, Stability of nonlinear systems
Abstract: This letter proposes a passivity based integral sliding mode controller for mechanical port-Hamiltonian systems. Recently, passivity based sliding mode control (PBSMC) has been proposed for mechanical and electro-mechanical systems. This method has properties of both sliding mode control (SMC) and passivity based control. However, the robustness of SMC is not guaranteed in the reaching phase and so is PBSMC. For this problem, integral sliding mode control (ISMC), which eliminates the reaching phase, has been proposed. This letter proposes unified control method of passivity based control and integral sliding mode control based on the idea of PBSMC. In order to achieve ISMC in the port-Hamiltonian form, an integral term of the sliding variable of PBSMC is firstly added to the system equation. Next, by adding appropriate potential function to the Hamiltonian function, the dynamics of ISMC can be obtained. Proposed method is more robust than PBSMC and ensures Lyapunov stability when the chattering phenomena is alleviated. The effectiveness of the proposed method is demonstrated by a numerical example.
|
|
14:30-14:50, Paper FrB24.4 | |
>Design of a Deep Neural Network-Based Integral Sliding Mode Control for Nonlinear Systems under Fully Unknown Dynamics |
|
Vacchini, Edoardo | University of Pavia |
Sacchi, Nikolas | University of Pavia |
Incremona, Gian Paolo | Politecnico Di Milano |
Ferrara, Antonella | University of Pavia |
Keywords: Variable-structure/sliding-mode control, Neural networks, Uncertain systems
Abstract: In this paper a novel deep neural network based integral sliding mode (DNN-ISM) control is proposed for controlling perturbed systems with fully unknown dynamics. In particular, two DNNs with an arbitrary number of hidden layers are exploited to estimate the unknown drift term and the control effectiveness matrix of the system, which are instrumental to design the ISM controller. The DNNs weights are adjusted according to adaptation laws derived directly from Lyapunov stability analysis, and the proposal is satisfactorily assessed in simulation relying on benchmark examples.
|
|
14:50-15:10, Paper FrB24.5 | |
>Structural Conditions for Chattering Avoidance in Implicitly Discretized Sliding Mode Differentiators |
|
Seeber, Richard | Graz University of Technology |
Koch, Stefan | Graz University of Technology |
Keywords: Variable-structure/sliding-mode control, Sampled-data control, Estimation
Abstract: The present paper considers the implicit discretization of Levant's arbitrary order robust exact differentiator. It is shown that an improper implicit discretization may lead to an undesired bias in the differentiation error and, surprisingly, to discretization chattering despite the implicit discretization. Necessary and sufficient structural conditions for avoiding both of these problems are presented, which define a family of chattering-free discrete-time differentiators. A guideline for selecting a representative from this family is given. Numerical simulations illustrate the results.
|
|
15:10-15:30, Paper FrB24.6 | |
>A Robust Interval MPC for Uncertain LPV Systems Via Integral Sliding–Mode Control |
|
Gutierrez, Susana | FIME-UANL |
Ríos, Héctor | Tecnológico Nacional De México/I.T. La Laguna |
Mera, Manuel | Esime Upt Ipn |
Raïssi, Tarek | Conservatoire National Des Arts Et Métiers |
Efimov, Denis | Inria |
Keywords: Linear parameter-varying systems, Variable-structure/sliding-mode control, Constrained control
Abstract: This paper presents the design of a robust control strategy for linear parameter–varying (LPV) systems. The proposed strategy involves the design of a robust control law based on an integral sliding–mode control (ISMC) approach with an interval predictor-based state feedback controller and a Model Predictive Control (MPC) scheme. The proposed controller is robust to some external disturbances and parameter uncertainties and deals with state and input constraints. The integral sliding–mode compensates for matched perturbations starting from the initial moment, i.e., ensuring the sliding–mode from the initial time instance. Then, the interval predictor–based state feedback controller and the MPC deal with the state and input constraints. The proposed strategy guarantees the exponential stability of the system. Furthermore, the simulation results show high performance of the proposed controller.
|
|
FrB25 |
Lotus Junior 4DE |
Security, Safety and Resilience of Discrete Event Systems |
Invited Session |
Chair: Yin, Xiang | Shanghai Jiao Tong University |
Co-Chair: Cai, Kai | Osaka Metropolitan University |
Organizer: Yin, Xiang | Shanghai Jiao Tong University |
Organizer: Cai, Kai | Osaka Metropolitan University |
|
13:30-13:50, Paper FrB25.1 | |
>Edit Mechanism Synthesis for Opacity Enforcement under Uncertain Observations |
|
Duan, Wei | Xidian Universisty |
Liu, Ruotian | Polytechnic University of Bari |
Fanti, Maria Pia | Polytechnic of Bari |
Hadjicostis, Christoforos N. | University of Cyprus |
Li, Zhiwu | Xidian University |
Keywords: Discrete event systems, Automata, Game theory
Abstract: This paper addresses the problem of opacity enforcement by using edit functions in discrete event systems modeled as deterministic finite automata under partial observation. The edit function is an output interface of the system that manipulates actual observations to confuse a malicious intruder. We assume that the edit function simply knows whether the intruder observes a larger or smaller set of events than itself, but does not know the exact set of events observed by the intruder. In this uncertain observation setting, the edit function aims to confuse the intruder while relying on its own set of observable events, which requires the edit function to be u-enforcing. The opacity enforcement problem is then transformed to a two-player game between the system and the edit function under partial information. A so-called edit mechanism is proposed in a game scheme to enumerate all possible edited operations following the system behavior. We show that an edit function synthesized from the edit mechanism (if any) can be used to enforce opacity in the system under the uncertain observation setting.
|
|
13:50-14:10, Paper FrB25.2 | |
>Security-Preserving Multi-Robot Path Planning for Boolean Specification Tasks Using Labeled Petri Nets |
|
Shi, Weijie | Shaanxi University of Science and Technology |
He, Zhou | Shaanxi University of Science and Technology |
Ma, Ziyue | Xidian University |
Ran, Ning | Hebei University |
Yin, Xiang | Shanghai Jiao Tong University |
Keywords: Discrete event systems, Petri nets, Optimal control
Abstract: This letter investigates the path planning of multirobot systems for high-level tasks described by Boolean specifications and security constraints. We assume that the behavior of each robot can be identified and partially monitored by a passive intruder. The problem aims to plan an optimal path for each robot such that the tasks expressed in conjunction, disjunction, and negation for trajectories and final states are coordinately completed. The security constraints require that the intruder should never infer the final locations of a set of robots called secret robots. In order to solve this problem, labeled Petri nets are adopted to model the mobile capability of the multirobot systems. Then an integer linear programming problem is proposed to find an optimal solution (if it exists) such that the Boolean specification is fulfilled, while the securities of secret robots are preserved. Finally, the effectiveness of the proposed method is illustrated through several simulation studies.
|
|
14:10-14:30, Paper FrB25.3 | |
>Supervisor Fortification against Covert Actuator Attacks (I) |
|
Tai, Ruochen | Nanyang Technological University |
Lin, Liyong | Nanyang Technological University |
Su, Rong | Nanyang Technological University |
Keywords: Discrete event systems, Supervisory control, Cyber-Physical Security
Abstract: This work considers the supervisor fortification problem against covert actuator attacks. A supervisor S' is said to fortify the supervisor S, the latter of which is non-resilient against covert actuator attacks, if S' satisfies two conditions: 1) any covert actuator attack cannot cause damage infliction against S', and 2) S' is control equivalent to S. The key result of this work is that we show the problem of determining the existence of a fortified supervisor to defend against any covert actuator attack, an "exist-for all" decidability question, is decidable. To show the decidability result, we provide a complete and sound procedure that ensures to synthesize a fortified supervisor as long as there exists one.
|
|
14:30-14:50, Paper FrB25.4 | |
>Fault Diagnosis of Discrete Event Systems under Attack (I) |
|
Kang, Tenglong | Xidian University |
Seatzu, Carla | Univ. of Cagliari |
Li, Zhiwu | Xidian University |
Giua, Alessandro | University of Cagliari |
Keywords: Discrete event systems, Automata, Fault diagnosis
Abstract: In this paper, we study the problem of fault diagnosis under cyber attacks in the context of partially-observed discrete event systems. An operator monitors the evolution of a system through the received observations and computes its current diagnosis state. The observation is corrupted by an attacker which has the ability to edit a subset of sensor readings by inserting or erasing some events. In this sense, the attacker may induce the operator to draw incorrect diagnostic conclusions based on the corrupted observation regarding the fault occurrence. In particular, the attack is harmful if a fault can be detected by the operator when looking at an uncorrupted observation, while it is not detected when looking at the corresponding corrupted observation. In addition, the attacker must remain stealthy, i.e., its presence should not be discovered by the operator. We propose a special structure, called a stealthy joint diagnoser, which describes the set of all possible stealthy attacks. We show how to use the stealthy joint diagnoser to perform fault diagnosis under attack. Finally, such a structure also allows one to establish if a stealthy harmful attack may be implemented.
|
|
14:50-15:10, Paper FrB25.5 | |
>Abstraction-Based Synthesis of Controllers for Approximate Opacity (I) |
|
Hou, Junyao | ShanghaiJiaoTong University |
Liu, Siyuan | KTH Royal Institute of Technology |
Yin, Xiang | Shanghai Jiao Tong University |
Zamani, Majid | University of Colorado Boulder |
Keywords: Discrete event systems, Supervisory control, Automata
Abstract: Opacity is an important information-flow security property which characterizes the plausible deniability of certain “secret behaviors” in dynamical systems. In this paper, we study the problem of synthesizing controllers enforcing a notion of opacity over discrete-time control systems with continuous state sets. It is known that, for systems with uncountable state sets, the opacity-enforcing controller synthesis problem is undecidable in general. To address this undecidability issue, in this paper, we develop an abstraction-based approach to tackle the controller synthesis problem. Specifically, we adopt a notion of approximate opacity which is suitable for continuous-space control systems. We propose a notion of approximate initial- state opacity preserving alternating simulation relation which characterizes the closeness between two systems in terms of opacity preservation. We show that, based on this new notion of system relation, one can synthesize an opacity-enforcing controller for the abstract system which is finite and then refine it back to enforce opacity over the original control system. Finally, we present a method for constructing opacity- preserving finite abstractions for discrete-time control systems under some stability properties. Our results are illustrated on a two-room temperature control problem.
|
|
15:10-15:30, Paper FrB25.6 | |
>Towards Supervisory Control Theory in Tactical Environments: A Stackelberg Game Approach (I) |
|
Cui, Bohan | Shanghai Jiao Tong University |
Giua, Alessandro | University of Cagliari |
Yin, Xiang | Shanghai Jiao Tong University |
Keywords: Discrete event systems, Supervisory control, Automata
Abstract: In this paper, we propose a new framework for supervisory control of discrete-event systems in tactical environments. In contrast to the standard supervisory control theory, where the environments are considered fully adversarial, we consider the possibility of the presence of attackers who have their own objectives that may not necessarily be in opposition to the specification of the supervisor. We formulate this scenario as a Stakelberg game in the leader-follower setting, where the designer proposes a supervisor, and the attacker takes a best response to the supervisor. We characterize the solution to the Stakelberg supervisory control problem as having both cooperative and antagonistic solutions. Moreover, we provide an effective algorithm for synthesizing a cooperative supervisor that enables both players to achieve their objectives. Our work makes an initial step forward from the traditional zerosum setting of supervisory control theory to the non-zero-sum setting. Examples are provided to illustrate our results.
|
|
FrC01 |
Melati Junior 4010A-4111 |
Learning, Optimization, and Game Theory V |
Invited Session |
Chair: Vamvoudakis, Kyriakos G. | Georgia Inst. of Tech |
Co-Chair: Doan, Thinh T. | Virginia Tech |
Organizer: Doan, Thinh T. | Virginia Tech |
Organizer: Sayin, Muhammed Omer | Bilkent University |
Organizer: Vamvoudakis, Kyriakos G. | Georgia Inst. of Tech |
Organizer: Zhang, Kaiqing | University of Maryland |
|
16:00-16:20, Paper FrC01.1 | |
>Reinforcement-Learning-Based Risk-Sensitive Optimal Feedback Mechanisms of Biological Motor Control (I) |
|
Cui, Leilei | New York University |
Pang, Bo | New York University |
Jiang, Zhong-Ping | New York University |
Keywords: Data driven control, Biological systems, Optimal control
Abstract: Risk sensitivity is a fundamental aspect of biological motor control that accounts for both the expectation and variability of movement cost in the face of uncertainty. However, most computational models of biological motor control rely on model-based risk-sensitive optimal control, which requires an accurate internal representation in the central neural system to predict the outcomes of motor commands. In reality, the dynamics of human-environment interaction is too complex to be accurately modeled, and noise further complicates system identification. To address this issue, this paper proposes a novel risk-sensitive computational mechanism for biological motor control based on reinforcement learning (RL) and adaptive dynamic programming (ADP). The proposed ADP-based mechanism suggests that humans can directly learn an approximation of the risk-sensitive optimal feedback controller from noisy sensory data without the need for system identification. Numerical validation of the proposed mechanism is conducted on the arm-reaching task under divergent force field. The preliminary computational results align with the experimental observations from the past literature of computational neuroscience.
|
|
16:20-16:40, Paper FrC01.2 | |
>Adaptive Optimal Output Regulation of Discrete-Time Linear Systems: A Reinforcement Learning Approach (I) |
|
Chakraborty, Sayan | New York University |
Gao, Weinan | Northeastern University |
Vamvoudakis, Kyriakos G. | Georgia Inst. of Tech |
Jiang, Zhong-Ping | New York University |
Keywords: Optimal control, Output regulation
Abstract: In this paper, we solve the optimal output regulation problem for discrete-time systems without precise knowledge of the system model. Drawing inspiration from reinforcement learning and adaptive dynamic programming, a data-driven solution is developed that enables asymptotic tracking and disturbance rejection. Notably, it is discovered that the proposed approach for discrete-time output regulation differs from the continuous-time approach in terms of the persistent excitation condition required for policy iteration to be unique and convergent. To address this issue, a new persistent excitation condition is introduced to ensure both uniqueness and convergence of the data-driven policy iteration. The efficacy of the proposed methodology is validated by an inverted pendulum on a cart example.
|
|
16:40-17:00, Paper FrC01.3 | |
>Online Learning for Incentive-Based Demand Response (I) |
|
Muthirayan, Deepan | University of California at Irvine |
Khargonekar, Pramod | Univ. of California, Irvine |
Keywords: Learning, Agents-based systems, Energy systems
Abstract: In this paper, we consider the problem of learning online to manage Demand Response (DR) resources. A typical DR mechanism requires the DR manager to assign a baseline to the participating consumer, where the baseline is an estimate of the counterfactual consumption of the consumer had it not been called to provide the DR service. A challenge of estimating the baseline is the incentive the consumers have to inflate the baseline. We consider the problem of learning online to estimate the baseline and to optimize the operating costs over a period of time under such incentives. We propose an online learning scheme that employs least-squares for estimation with a perturbation to the reward price (for the DR services or load curtailment) that is designed to balance the exploration and exploitation trade-off that arises with online learning. We show that, our proposed scheme is able to achieve a very low regret of mathcal{O}left((log{T})^2right) with respect to the optimal operating cost over T days of the DR program with full knowledge of the baseline, and is individually rational for the consumers to participate. Our scheme is significantly better than the averaging type approach, which only fetches mathcal{O}(T^{1/3}) regret.
|
|
17:00-17:20, Paper FrC01.4 | |
>Game-Theoretic Deception Methods for Perfectly and Bounded Rational Stealthy Attackers (I) |
|
Fotiadis, Filippos | Georgia Institute of Technology |
Vamvoudakis, Kyriakos G. | Georgia Inst. of Tech |
Keywords: Game theory, Cyber-Physical Security, Agents-based systems
Abstract: In this paper, we consider a system that is under the effect of multiple stealthy attackers, whose inputs we design using perfectly and imperfectly rational game-theoretic approaches. The goal of the attackers is to steer the state of the system as far as possible from the origin, so as to disrupt the nominal objective of system regulation. However, to remain stealthy, the attackers must ensure that the total magnitude of their inputs remains below a certain threshold, otherwise they are at risk of being exposed to a detection mechanism that monitors the system. To derive the optimal attack policies for the attackers, we interpret the aforementioned setup as a constrained game, and we solve it in two cases: in the first case, we assume that the attackers are perfectly rational and operate on the Nash equilibrium, which we derive in closed-form; and in the second case, we assume that the attackers are imperfectly rational, and we design two models of bounded rationality as a means to capture their different levels of rationality. Under certain conditions, it is proved that the corresponding bounded rationality models converge to a Nash equilibrium as the levels of rationality increase. Simulations demonstrate the efficiency of the derived attack policies in both the perfectly and the imperfectly rational case.
|
|
17:20-17:40, Paper FrC01.5 | |
>Maximizing Reachability in Factored MDPs Via Near-Optimal Clustering with Applications to Control of Multi-Agent Systems (I) |
|
Fiscko, Carmel | Washington University in St Louis |
Kar, Soummya | Carnegie Mellon University |
Sinopoli, Bruno | Washington University in St Louis |
Keywords: Markov processes, Agents-based systems, Stochastic systems
Abstract: We consider cluster-based control of agents modeled as a transition-independent Markov decision process (MDP), and the objective of assigning agents to clusters to maximize the size of the reachable state space. This goal is relevant to applications for which the same MDP model may be used to compute policies for different reward functions. The system controller wishes to define clusters to maximize flexibility within the attainable outcomes. Under the transition-independent MDP formulation, we first show that the size of the reachable state space is a submodular function. While maximizing the reachable state space subject to a desired number of clusters is a hard problem, properties of submodular optimization can be leveraged to propose approximate clustering techniques. We next demonstrate that a greedy clustering approach is a viable approximate solution and has a bounded optimality gap. We compare the performance in terms of value and computation complexity in using the flexibility-optimized clustering assignment versus a clustering assignment optimized for a specific reward function; there will be a loss in value at a savings in complexity. Finally, we demonstrate the utility of the flexibility-optimized clustering assignment in simulation on the same MDP model with various reward functions.
|
|
17:40-18:00, Paper FrC01.6 | |
>An Observer-Based Reinforcement Learning Solution for Model-Following Problems (I) |
|
Abouheaf, Mohammed | Bowling Green State University |
Vamvoudakis, Kyriakos G. | Georgia Inst. of Tech |
Mayyas, Mohammad | Bowling Green State University |
Hashim, Hashim A | Carleton University |
Keywords: Machine learning, Adaptive systems, Optimal control
Abstract: This paper introduces a novel model-free solution for a multi-objective model-following control problem, utilizing an observer-based adaptive learning approach. The goal is to regulate model-following error dynamics and optimize process variables simultaneously. Integral reinforcement learning is employed to adapt three key strategies, including observation, closed-loop stabilization, and reference trajectory tracking. Implementation uses an approximate projection estimation method under mild conditions on learning parameters.
|
|
FrC02 |
Orchid Main 4202-4303 |
Data-Driven Verification and Control of Cyber-Physical Systems III |
Invited Session |
Chair: Zamani, Majid | University of Colorado Boulder |
Co-Chair: Lavaei, Abolfazl | Newcastle University |
Organizer: Lavaei, Abolfazl | Newcastle University |
Organizer: Jungers, Raphaël M. | University of Louvain |
Organizer: Abate, Alessandro | University of Oxford |
|
16:00-16:20, Paper FrC02.1 | |
>Star Based Reachability Analysis of Interval Neural Networks (I) |
|
Bondalakunta, Vishnu | Kansas State University |
Prabhakar, Pavithra | Kansas State University |
Keywords: Formal Verification/Synthesis
Abstract: The paper explores the computation of output reachable sets for Interval Neural Networks (INNs) with ReLU activation functions. An INN is a generalization of a Neural Network (NN), where the weights and biases are intervals rather than numbers. We propose a novel algorithm for computing precise over-approximations of the output reachable sets for INNs by introducing a novel data structure called interval star set which is a generalized version of the star set. Specifically, when the INN is a traditional NN, our method reduces to the standard star-based verification of NNs. We present experimental results that demonstrate that our method outperforms the existing method based on mixed integer linear programming (MILP) for the problem of INN output reachable set computation.
|
|
16:20-16:40, Paper FrC02.2 | |
>Data-Driven Safe Controller Synthesis for Deterministic Systems: A Posteriori Method with Validation Tests (I) |
|
Chen, Yu | Shanghai Jiao Tong University |
Shang, Chao | Tsinghua University |
Huang, Xiaolin | Shanghai Jiao Tong University |
Yin, Xiang | Shanghai Jiao Tong University |
Keywords: Formal Verification/Synthesis, Data driven control
Abstract: In this work, we investigate the data-driven safe control synthesis problem for unknown dynamic systems. We first formulate the safety synthesis problem as a robust convex program (RCP) based on notion of control barrier function. To resolve the issue of unknown system dynamic, we follow the existing approach by converting the RCP to a scenario convex program (SCP) by randomly collecting finite samples of system trajectory. However, to improve the sample efficiency to achieve a desired confidence bound, we provide a new posteriori method with validation tests. Specifically, after collecting a set of data for the SCP, we further collect another set of independent validate data as posterior information to test the obtained solution. We derive a new overall confidence bound for the safety of the controller that connects the original sample data, the support constraints, and the validation data. The efficiency of the proposed approach is illustrated by a case study of room temperature control. We show that, compared with existing methods, the proposed approach can significantly reduce the required number of sample data to achieve a desired confidence bound
|
|
16:40-17:00, Paper FrC02.3 | |
>Symbolic Abstractions with Guarantees: A Data-Driven Divide-And-Conquer Strategy (I) |
|
Lavaei, Abolfazl | Newcastle University |
Keywords: Data driven control, Large-scale systems, Formal Verification/Synthesis
Abstract: This article is concerned with a data-driven divide-and-conquer strategy to construct symbolic abstractions for interconnected control networks with unknown mathematical models. We employ a notion of alternating bisimulation functions (ABF) to quantify the closeness between state trajectories of an interconnected network and its symbolic abstraction. Consequently, the constructed symbolic abstraction can be leveraged as a beneficial substitute for the formal verification and controller synthesis over the interconnected network. In our data-driven framework, we first establish a relation between each unknown subsystem and its data-driven symbolic abstraction, so-called alternating pseudo-bisimulation function (APBF), with a guaranteed probabilistic confidence. We then provide compositional conditions based on max-type small-gain techniques to construct an ABF for an unknown interconnected network using APBF of its individual subsystems, constructed from data. We demonstrate the efficacy of our data-driven approach over a room temperature network composing 100 rooms with unknown models. We construct a symbolic abstraction from data for each room as an appropriate substitute of original system and compositionally synthesize controllers regulating the temperature of each room within a safe zone with some guaranteed probabilistic confidence.
|
|
17:00-17:20, Paper FrC02.4 | |
>Transfer Learning for Barrier Certificates (I) |
|
Nadali, Alireza | University of Colorado, Boulder |
Trivedi, Ashutosh | University of Colorado Boulder |
Zamani, Majid | University of Colorado Boulder |
Keywords: Learning, Formal Verification/Synthesis, Neural networks
Abstract: A principled approach to safety verification of dynamical systems demands formal guarantees. Barrier certificates are an effective tool for searching safety proofs in the form of inductively verifiable invariants. However, finding barrier certificates is an expensive and time-consuming process that demands human expertise in selecting various templates, hyperparameters, and decision procedures. Is it possible to transfer the knowledge gained in finding a barrier certificate and control algorithm from a given environment source environment to a different but related environment target environment? This paper presents a transfer learning approach to adapt the barrier certificates (of any template) in the form of neural networks from the source to the target environment. We derive a validity condition to formally guarantee the correctness of network by leveraging its Lipschitz continuity. To demonstrate the effectiveness of our approach, we apply it to two case studies, namely the inverted pendulum and DC motor. Our results show that transfer learning can successfully adapt barrier certificates from the source to the target environment, reducing the need for human expertise and speeding up the verification process.
|
|
17:20-17:40, Paper FrC02.5 | |
>Abstraction-Based Safety Analysis of Linear Dynamical Systems with Neural Network Controllers (I) |
|
Lal, Ratan | Northwest Missouri State University |
Prabhakar, Pavithra | Kansas State University |
Keywords: Neural networks, Linear systems, Formal Verification/Synthesis
Abstract: We consider the safety verification problem of a closed-loop discrete-time linear dynamical system with a neural network controller. The crux of safety verification relies on computing output reachable sets of the dynamical system and the neural network. Reachable set computation time of the neural network grows with the network size. To address the scalability issue, our main approach consists of abstracting the neural network controller into a smaller emph{annotated interval neural network} (AINN), and using this to compute an over-approximation of the reachable set of the closed-loop system. We present a novel approach for output reachable set computation of an AINN by decomposing it into two reachable set computation problems on neural networks, which we then compute using star-sets. Our experimental analysis on two benchmarks demonstrate the trade-off in the precision and time for reachable set computation.
|
|
17:40-18:00, Paper FrC02.6 | |
>Towards Learning and Verifying Maximal Neural Lyapunov Functions (I) |
|
Liu, Jun | University of Waterloo |
Meng, Yiming | University of Waterloo |
Fitzsimmons, Maxwell | University of Waterloo |
Zhou, Ruikun | University of Waterloo |
Keywords: Formal Verification/Synthesis, Learning, Stability of linear systems
Abstract: The search for Lyapunov functions is a crucial task in the analysis of nonlinear systems. In this paper, we present a physics-informed neural network (PINN) approach to learning a Lyapunov function that is nearly maximal for a given stable set. A Lyapunov function is considered nearly maximal if its sub-level sets can be made arbitrarily close to the boundary of the domain of attraction. We use Zubov's equation to train a maximal Lyapunov function defined on the domain of attraction. Additionally, we propose conditions that can be readily verified by satisfiability modulo theories (SMT) solvers for both local and global stability. We provide theoretical guarantees on the existence of maximal Lyapunov functions and demonstrate the effectiveness of our computational approach through numerical examples.
|
|
FrC03 |
Orchid Main 4204-4305 |
Cyber-Physical Systems: Privacy and Security of Networked Systems |
Invited Session |
Chair: Sadabadi, Mahdieh S. | Queen Mary University of London |
Co-Chair: Escudero, Cédric | INSA Lyon, Laboratoire Ampère |
Organizer: Sadabadi, Mahdieh S. | University of Manchester |
Organizer: Escudero, Cédric | INSA Lyon, Laboratoire Ampère |
Organizer: Selvi, Daniela | Università Di Pisa |
Organizer: Soudjani, Sadegh | Newcastle University |
Organizer: Murguia, Carlos | Eindhoven University of Technology |
Organizer: Chong, Michelle | Eindhoven University of Technology |
Organizer: Ferrari, Riccardo M.G. | Delft University of Technology |
Organizer: Sasahara, Hampei | Tokyo Institute of Technology |
Organizer: Zhu, Quanyan | New York University |
|
16:00-16:20, Paper FrC03.1 | |
>Secure State Estimation under Actuator and Sensor Attacks Using Sliding Mode Observers |
|
Keijzer, Twan | Delft University of Technology |
Ferrari, Riccardo M.G. | Delft University of Technology |
Sandberg, Henrik | KTH Royal Institute of Technology |
Keywords: Large-scale systems, Networked control systems, Fault diagnosis
Abstract: Interconnections in modern systems make them vulnerable to adversarial attackers both by corrupting communication channels and compromising entire subsystems. The field of secure state estimation (SSE) aims to provide correct state estimation even when an unknown part of the measurement signals is corrupted. In this paper, we propose a solution to a novel generalized SSE problem in which full subsystems can be compromised, corrupting both the actuation and measurement signals. For a full system with p measurements, the proposed sliding mode observer (SMO)-based solution allows for up to p attack channels which can be arbitrarily distributed amongst attacks on actuation and measurement signals. This is a much larger class of attacks than considered in the existing literature. The method is demonstrated on 10 interconnected mass-spring-damper subsystems.
|
|
16:20-16:40, Paper FrC03.2 | |
>On the Trade-Offs between Accuracy, Privacy, and Resilience in Average Consensus Algorithms (I) |
|
Ramos, Guilherme | Instituto De Telecomunicações, 1049-001 Lisbon, Portugal |
Teixeira, André M. H. | Uppsala University |
Pequito, Sergio | Uppsala University |
Keywords: Network analysis and control, Control applications, Estimation
Abstract: There can be none. In this paper, we address the problem of a set of discrete-time networked agents reaching average consensus privately and resiliently in the presence of a subset of attacked agents. Existing approaches to the problem rely on trade-offs between accuracy, privacy, and resilience, sacrificing one for the others. We show that a separation-like principle for privacy-preserving and resilient discrete-time average consensus is possible. Specifically, we propose a scheme that combines strategies from resilient average consensus and private average consensus, which yields both desired properties. The proposed scheme has polynomial time-complexity on the number of agents and the maximum number of attacked agents. In other words, each agent that is not under attack is able to detect and discard the values of the attacked agents, reaching the average consensus of non-attacked agents while keeping each agent’s initial state private. Finally, we demonstrate the effectiveness of the proposed method with numerical results.
|
|
16:40-17:00, Paper FrC03.3 | |
>Privacy-Informed Consensus-Based Secondary Control in Cyber-Physical DC Microgrids |
|
Sadabadi, Mahdieh S. | University of Manchester |
Keywords: Power electronics, Distributed control, Linear systems
Abstract: This letter proposes a privacy-informed consensus-based distributed secondary control strategy for cyber-physical dc microgrids. The proposed secondary control approach relies on output masks that transform the physical states of distributed generation (DG) units to some auxiliary states by adding local perturbation signals, whose functional form and parameters are local and chosen independently by each DG unit. The proposed privacy-preserving secondary control scheme ensures voltage balancing and proportional current sharing in dc microgrids without disclosing the physical states of distributed generation units to their neighbors. Simulation case studies confirm the theoretical results of this letter.
|
|
17:00-17:20, Paper FrC03.4 | |
>Privacy-Engineered Value Decomposition Networks for Cooperative Multi-Agent Reinforcement Learning (I) |
|
Gohari, Parham | The University of Texas at Austin |
Hale, Matthew | University of Florida |
Topcu, Ufuk | The University of Texas at Austin |
Keywords: Control Systems Privacy, Agents-based systems, Machine learning
Abstract: In cooperative multi-agent reinforcement learning (Co-MARL), a team of agents must jointly optimize the team's long-term rewards to learn a designated task. Optimizing rewards as a team often requires inter-agent communication and data sharing, leading to potential privacy implications. We assume privacy considerations prohibit the agents from sharing their environment interaction data. Accordingly, we propose Privacy-Engineered Value Decomposition Networks (PE-VDN), a Co-MARL algorithm that models multi-agent coordination while provably safeguarding the confidentiality of the agents' environment interaction data. We integrate three privacy-engineering techniques to redesign the data flows of the VDN algorithm—an existing Co-MARL algorithm that consolidates the agents' environment interaction data to train a central controller that models multi-agent coordination—and develop PE-VDN. In the first technique, we design a distributed computation scheme that eliminates vanilla VDN's dependency on sharing environment interaction data. Then, we utilize a privacy-preserving multi-party computation protocol to guarantee that the data flows of the distributed computation scheme do not pose new privacy risks. Finally, we enforce differential privacy to preempt inference threats against the agents' training data—past environment interactions—when they take actions based on their neural network predictions. We implement PE-VDN in StarCraft Multi-Agent Competition (SMAC) and show that it achieves 80% of vanilla VDN's win rate while maintaining differential privacy levels that provide meaningful privacy guarantees. The results demonstrate that PE-VDN can safeguard the confidentiality of agents' environment interaction data without sacrificing multi-agent coordination.
|
|
17:20-17:40, Paper FrC03.5 | |
>Privacy Assessment for Linear Consensus Using Constrained Convex Generators (I) |
|
Silvestre, Daniel | NOVA University of Lisbon |
Keywords: Identification, Linear systems, Agents-based systems
Abstract: The problem of designing privacy-preserving algorithms for multi-agent systems running distributed algorithms has attracted the attention of the Control community, especially for maintaining the privacy of the initial state. In this paper, we tackle the problem of checking the privacy of the algorithm itself in terms of the linear parameters used by each agent. We first start by introducing a metric of privacy that translates the uncertainty that an attacker has related to the parameters for the case that it can eavesdrop the state from other agents given the public nature of the network. We then propose to resort to techniques in the literature to compute such metric and show how these can be used by: i) the attacker to estimate the parameters from successive runs of the algorithm; ii) by a defender that can decide when to trigger a negotiation of new parameters to ensuse privacy of the overall system. The technique is illustrated in simulations for the specific example of a consensus protocol. The tools developed herein can complement resilient consensus algorithms based on reputation metrics in the sense that the defender triggering changes to the dynamics while maintaining the overall convergence value can render the calculations of the optimal attacks rather troublesome.
|
|
17:40-18:00, Paper FrC03.6 | |
>Structural Analysis and Design for Security against Stealthy Attacks in Uncertain Systems (I) |
|
Zhang, Kangkang | Imperial College London |
Kasis, Andreas | University of Cyprus |
Polycarpou, Marios M. | University of Cyprus |
Parisini, Thomas | Imperial College & Univ. of Trieste |
Keywords: Fault diagnosis, Fault detection, Fault tolerant systems
Abstract: This paper considers the existence of stealthy integrity attacks for uncertain cyber-physical systems from a geometric point of view. We derive geometric structural conditions for the existence of stealthy integrity attacks and deduce the minimal actuator communication channels that, when protected, no stealthy integrity attacks exists. To examine different knowledge disclosure conditions for the attacker, we consider: (a) the attacker has full knowledge of the system linear terms but only the structure of the uncertain term, and (b) the attacker only knows the structures of the linear terms and the uncertain non-linear term. For scenario (a), the obtained existence condition of stealthy integrity attacks is that the uncertainty is decoupled with the maximal output-zeroing controlled-invariant subspace. In scenario (b), a graph is used to describe the uncertain system and we show that the existence of stealthy attacks is only possible if the uncertainty is decoupled with the fixed maximal output-zeroing controlled-invariant subspace. For each disclosure scenario, we deduce the minimum actuator communication channels to protect for guaranteeing the absence of stealthy integrity attacks. Our results are validated with a numerical example.
|
|
FrC04 |
Simpor Junior 4913 |
Traffic Control |
Regular Session |
Chair: Delle Monache, Maria Laura | University of California, Berkeley |
Co-Chair: Consolini, Luca | University of Parma |
|
16:00-16:20, Paper FrC04.1 | |
>Near Collision and Controllability Analysis of Nonlinear Optimal Velocity Follow-The-Leader Dynamical Model in Traffic Flow |
|
Nick Zinat Matin, Hossein | University of California, Berkeley |
Delle Monache, Maria Laura | University of California, Berkeley |
Keywords: Traffic control, Autonomous vehicles, Nonlinear systems
Abstract: This paper examines the optimal velocity follow-the-leader dynamics, a microscopic traffic model, and explores different aspects of the dynamical model, with particular emphasis on collision analysis. More precisely, we present a rigorous boundary-layer analysis of the model which provides a careful understanding of the behavior of the dynamics in trade-off with the singularity of the model at collision which is essential in the controllability of the system.
|
|
16:20-16:40, Paper FrC04.2 | |
>Boundary Stabilization for Mixed Traffic Flow in the Presence of Autonomous Vehicle Platooning |
|
Zhan, Jingyuan | Beijing University of Technology |
Wu, Jiahao | Beijing University of Technology |
Zhang, Liguo | Beijing University of Technology |
Keywords: Traffic control, Distributed parameter systems, Autonomous vehicles
Abstract: This paper investigates the boundary stabilization problem for a mixed traffic flow system composed of the traditional human-driven traffic flow and a platoon of autonomous vehicles. Firstly, we employ the first-order LWR model to describe the mixed traffic flow, which is with a bilateral moving spatial domain governed by the platoon. In order to stabilize the mixed traffic flow into the desired density and platoon length, a downstream boundary controller is designed based on the information of upstream density and platoon length. To facilitate the well-posedness and stabilization analysis, we transform the system into a coupled PDE-ODE system with fixed spatial domain. Then we prove the well-posedness of the system, and we further derive sufficient conditions for ensuring the local exponential stability of the system by employing the Lyapunov function method. Finally, numerical simulations are provided to validate the theoretical results.
|
|
16:40-17:00, Paper FrC04.3 | |
>Toward Efficient Traffic Signal Control: Smaller Network Can Do More |
|
Li, Shuya | Tsinghua University |
Mei, Hao | New Jersey Institue of Technology |
Li, Jianwei | Moffett.AI |
Wei, Hua | Arizona State University |
Xu, Dongkuan | North Carolina State University |
Keywords: Traffic control, Machine learning, Neural networks
Abstract: Reinforcement learning (RL)-based traffic signal control (TSC) optimizes signal switches through RL agents, adapting to intersection updates. Yet, existing RL-based TSC methods often demand substantial storage and computation resources, impeding real-world implementation. This study introduces a two-stage approach to compress the network, maintaining performance. Firstly, we identify a compact network via a removal-verification strategy. Secondly, pruning yields an even sparser network. In addition, Multi-task RL is adopted for multi-intersection TSC, reducing costs, and boosting performance. Our extensive evaluation shows a compressed network at 1/1432nd of original parameters, with an 11.2% enhancement over the best baseline. This work presents an efficient RL-based TSC solution for real-world contexts, offering insights into challenges and opportunities in the field.
|
|
17:00-17:20, Paper FrC04.4 | |
>Inducing Desired Equilibrium in Taxi Repositioning Problem with Adaptive Incentive Design |
|
Li, Jianhui | Zhejiang University |
Niu, Youcheng | Zhejiang University |
Li, Shuang | The Chinese University of Hong Kong, Shenzhen |
Li, Yuzhe | Northeastern University |
Xu, Jinming | Zhejiang University |
Wu, Junfeng | The Chinese Unviersity of Hong Kong, Shenzhen |
Keywords: Traffic control, Optimization algorithms, Network analysis and control
Abstract: We study the problem of designing incentives to induce desired equilibrium in taxi repositioning problems. In this scenario, self-interested idle drivers will update their repositioning strategies with observed payoff. Meanwhile, the platform will adaptively design incentives to induce a better Nash equilibrium for global efficiency. We formulate the problem as a bi-level optimization problem where the incentive designer and idle drivers simultaneously update their decision variables. We prove that agents' strategies will reach Nash equilibrium, and the incentive designer's objective function will reach optimality under Polyak Lojasiewicz (PL) condition. Furthermore, we derive a sufficient condition for the PL condition to hold for the upper-level objective function and lower-level agents' payoff function. Finally, we demonstrate the efficiency of the proposed method by numerical results.
|
|
17:20-17:40, Paper FrC04.5 | |
>Local Optimization of MAPF Solutions on Directed Graphs |
|
Ardizzoni, Stefano | University of Parma |
Saccani, Irene | Università Di Parma |
Consolini, Luca | Università Di Parma |
Locatelli, Marco | University of Parma |
Keywords: Optimization, Traffic control, Agents-based systems
Abstract: Among sub-optimal MAPF solvers, rule-based algorithms are particularly appealing since they are complete. Even in crowded scenarios, they allow finding a feasible solution that brings each agent to its target, preventing deadlock situations. However, generally, rule-based algorithms provide solutions that are much longer than the optimal one. The main contribution of this paper is the introduction of an iterative local search procedure in MAPF. We start from a feasible suboptimal solution and we perform a local search in a neighborhood of this solution, to find a shorter one. Iteratively, we repeat this procedure until the solution cannot be shortened any longer. At the end, we obtain a solution, that is still sub-optimal, but, in general, of much better quality than the initial one. We use dynamic programming for the local search procedure. Under this respect, the fact that our search is local is fundamental to reduce the time complexity of the algorithm. Indeed, if we apply a standard dynamic programming the number of explored states grows exponentially with the number of agents. As we will see, the introduction of a locality constraint allows solving the (local) dynamic programming problem in a time that grows only polynomially with respect to the number of agents.
|
|
17:40-18:00, Paper FrC04.6 | |
>Modeling Multiday Route Choices of Strategic Commuters: A Mean Field Game Approach |
|
Wu, Minghui | University of Michigan |
Yin, Yafeng | University of Michigan |
Lynch, Jerome | Duke University |
Keywords: Mean field games, Traffic control
Abstract: In the era of connected and automated mobility, commuters will possess strong computation capabilities, enabling them to make foresighted and strategic route choices. This paper investigates the implications of such strategic planning on traffic patterns by modeling the commute problem as a mean field game, where every traveler plans for sequential route choices over a span of several days. We examine the concept of multiday user equilibrium, a special mean field equilibrium under commuter interactions, to derive network traffic flow patterns. Under mild conditions, our analysis establishes the existence and uniqueness of the equilibrium flow pattern and explores its relationship with conventional Wardrop equilibrium.
|
|
FrC05 |
Simpor Junior 4912 |
Strategic Coordination in Multi-Agent Systems and Its Applications |
Invited Session |
Chair: Vasconcelos, Marcos M. | Florida State University |
Co-Chair: Park, Shinkyu | KAUST |
Organizer: Vasconcelos, Marcos M. | Florida State University |
Organizer: Park, Shinkyu | KAUST |
|
16:00-16:20, Paper FrC05.1 | |
>Scenario-Game ADMM: A Parallelized Scenario-Based Solver for Stochastic Noncooperative Games (I) |
|
Li, Jingqi | University of California, Berkeley |
Chiu, Chih-Yuan | University of California, Berkeley |
Peters, Lasse | Delft University of Technology |
Palafox Escobedo, Fernando | University of Texas at Austin |
Karabag, Mustafa O. | The University of Texas at Austin |
Alonso-Mora, Javier | Delft University of Technology |
Sojoudi, Somayeh | UC Berkeley |
Tomlin, Claire J. | UC Berkeley |
Fridovich-Keil, David | The University of Texas at Austin |
Keywords: Game theory, Decentralized control, Autonomous systems
Abstract: Decision making in multi-agent games can be extremely challenging, particularly under uncertainty. In this work, we propose a new sample-based approximation to a class of stochastic, general-sum, pure Nash games, where each player has an expected-value objective and a set of chance constraints. This new approximation scheme inherits the accuracy of objective approximation from the established sample average approximation (SAA) method and enjoys a feasibility guarantee derived from the scenario optimization literature. We characterize the sample complexity of this new game-theoretic approximation scheme, and observe that high accuracy usually requires a large number of samples, which results in a large number of sampled constraints. To accommodate this, we decompose the approximated game into a set of small-size games with few constraints for each sampled scenario, and propose a decentralized, consensus ADMM algorithm to efficiently compute a generalized Nash equilibrium of the approximated game. We prove the convergence of our algorithm and empirically demonstrate superior performance compared to a recent baseline.
|
|
16:20-16:40, Paper FrC05.2 | |
>Markov Games with Decoupled Dynamics: Price of Anarchy and Sample Complexity (I) |
|
Zhang, Runyu | Harvard University |
Zhang, Yuyang | Harvard University |
Konda, Rohit | UC Santa Barbara |
Ferguson, Bryce L. | University of California, Santa Barbara |
Marden, Jason R. | University of California, Santa Barbara |
Li, Na | Harvard University |
Keywords: Game theory, Markov processes, Learning
Abstract: This paper studies the finite-time horizon Markov games where the agents' dynamics are decoupled but the rewards can possibly be coupled across agents. The policy class is restricted to local policies where agents make decisions using their local state. We first introduce the notion of smooth Markov games which extends the smoothness argument for normal form games to our setting, and leverage the smoothness property to bound the price of anarchy of the Markov game. For a specific type of Markov game called the Markov potential game, we also develop a distributed learning algorithm, multi-agent soft policy iteration (MA-SPI), which provably converges to a Nash equilibrium. Sample complexity of the algorithm is also provided. Lastly, our results are validated using a dynamic covering game.
|
|
16:40-17:00, Paper FrC05.3 | |
>Factorization of Multi-Agent Sampling-Based Motion Planning (I) |
|
Zanardi, Alessandro | ETH Zurich |
Zullo, Pietro | ETH Zurich |
Censi, Andrea | ETH Zurich |
Frazzoli, Emilio | ETH Zürich |
Keywords: Autonomous robots, Robotics, Agents-based systems
Abstract: Modern robotics often involves multiple embodied agents operating within a shared environment. Path planning in these cases is considerably more challenging than in single-agent scenarios. Although standard Sampling-based Algorithms (SBAs) can be used to search for solutions in the robots’ joint space, this approach quickly becomes computationally intractable as the number of agents increases. To address this issue, we integrate the concept of factorization into sampling-based algorithms, which requires only minimal modifications to existing methods. During the search for a solution we can decouple (i.e., factorize) different subsets of agents into independent lower-dimensional search spaces once we certify that their future solutions will be independent of each other using a factorization heuristic. Consequently, we progressively construct a lean hypergraph where certain (hyper-)edges split the agents to independent subgraphs. In the best case, this approach can reduce the growth in dimensionality of the search space from exponential to linear in the number of agents. On average, fewer samples are needed to find high-quality solutions while preserving the optimality, completeness, and anytime properties of SBAs. We present a general implementation of a factorized SBA, derive an analytical gain in terms of sample complexity for PRM∗, and showcase empirical results for RRG.
|
|
17:00-17:20, Paper FrC05.4 | |
>Payoff Mechanism Design for Coordination in Multi-Agent Task Allocation Games (I) |
|
Park, Shinkyu | KAUST |
Barreiro-Gomez, Julian | New York University Abu Dhabi (NYUAD) |
Keywords: Game theory, Decentralized control, Agents-based systems
Abstract: We investigate a multi-agent decision-making problem where a large population of agents is responsible for carrying out a set of assigned tasks. The amount of jobs in each task varies over time governed by a dynamical system model. Each agent needs to select one of the available strategies to take on one or more tasks. Since each strategy allows an agent to perform multiple tasks at a time, possibly at distinct rates, the strategy selection of the agents needs to be coordinated. We formulate the problem using the population game formalism and refer to it as the task allocation game. We discuss the design of a decision-making model that incentivizes the agents to coordinate in the strategy selection process. As key contributions, we propose a method to find a payoff-driven decision-making model, and discuss how the model allows the strategy selection of the agents to be responsive to the amount of remaining jobs in each task while asymptotically attaining the optimal strategies. Leveraging analytical tools from feedback control theory, we derive technical conditions that the model needs to satisfy, which are used to construct a numerical approach to compute the model. We validate our solution through simulations to highlight how the proposed approach coordinates the agents in task allocation games.
|
|
17:20-17:40, Paper FrC05.5 | |
>Emergent Coordination through Game-Induced Nonlinear Opinion Dynamics (I) |
|
Hu, Haimin | Princeton University |
Nakamura, Kensuke | Princeton University |
Hsu, Kai-Chieh | Princeton University |
Leonard, Naomi Ehrich | Princeton University |
Fernández Fisac, Jaime | Princeton University |
Keywords: Distributed control, Game theory, Agents-based systems
Abstract: We present a multi-agent decision-making framework for the emergent coordination of autonomous agents whose intents are initially undecided. Dynamic non-cooperative games have been used to encode multi-agent interaction, but ambiguity arising from factors such as goal preference or the presence of multiple equilibria may lead to coordination issues, ranging from the ``freezing robot'' problem to unsafe behavior in safety-critical events. The recently developed nonlinear opinion dynamics (NOD) provide guarantees for breaking deadlocks. However, choosing the appropriate model parameters automatically in general multi-agent settings remains a challenge. In this paper, we first propose a novel and principled procedure for synthesizing NOD based on the value functions of dynamic games conditioned on agents’ intents. In particular, we provide for the two-player two-option case precise stability conditions for equilibria of the game-induced NOD based on the mismatch between agents' opinions and their game values. We then propose an optimization-based trajectory optimization algorithm that computes agents’ policies guided by the evolution of opinions. The efficacy of our method is illustrated with a simulated toll station coordination example.
|
|
17:40-18:00, Paper FrC05.6 | |
>On the Coordination Efficiency of Strategic Multi-Agent Robotic Teams (I) |
|
Vasconcelos, Marcos M. | Florida State University |
Touri, Behrouz | University of California San Diego |
Keywords: Game theory, Decentralized control, Agents-based systems
Abstract: We study the problem of achieving decentralized coordination by a group of strategic decision-makers choosing to engage or not in a task in a stochastic setting. First, we define a class of symmetric utility games that encompass a broad class of coordination games, including the popular framework known as textit{global games}. To study the extent to which agents engaging in a stochastic coordination game indeed coordinate, we propose a new probabilistic measure of coordination efficiency. Then, we provide a universal information-theoretic upper bound on the coordination efficiency as a function of the amount of noise in the observation channels. Finally, we revisit a large class of global games, and we illustrate that their Nash equilibrium policies may be less coordination efficient than certainty equivalent policies, despite them providing better expected utility. This counter-intuitive result, establishes the existence of a nontrivial trade-off between coordination efficiency and expected utility in coordination games.
|
|
FrC06 |
Simpor Junior 4911 |
Estimation and Control of Infinite Dimensional Systems III |
Invited Session |
Chair: Demetriou, Michael A. | Worcester Polytechnic Institute |
Co-Chair: Paranjape, Aditya A | Imperial College London |
Organizer: Demetriou, Michael A. | Worcester Polytechnic Institute |
Organizer: Burns, John A | Virginia Tech |
|
16:00-16:20, Paper FrC06.1 | |
>Finite-Dimensional Adaptive Observer Design for Reaction-Diffusion System (I) |
|
Ahmed-Ali, Tarek | ENSICAEN |
Fridman, Emilia | Tel-Aviv Univ |
Lamnabhi-Lagarrigue, Francoise | CNRS, Paris-Saclay University |
Keywords: Estimation, Distributed parameter systems, Adaptive systems
Abstract: A new finite dimensional adaptive observer is pro- posed for a class of infinite-dimensional systems. The observer is based on the modal decomposition approach and uses a classical persistent excitation condition to ensure exponential convergence of both states and parameter estimation errors to zero.
|
|
16:20-16:40, Paper FrC06.2 | |
>Modeling and Optimal Control for a Class of One Dimensional Counter-Swarm Problems with Distributed Point Actuation (I) |
|
Paranjape, Aditya A | Tata Consultancy Services Ltd |
Keywords: Distributed parameter systems, Agents-based systems, Optimal control
Abstract: This paper presents a class of counter-swarm problems wherein the mean-field behavior of the swarm is modeled as an infinite dimensional system. This work considers two classes of problems, one in which the spatial distribution of the agents is fixed and one in which it is dynamic and driven by the standard continuity equation in mechanics. The counter-swarm objectives are formulated as optimal control problems and solved numerically using deep Q-networks.
|
|
16:40-17:00, Paper FrC06.3 | |
>On Forwarding Techniques for Stabilization and Set-Point Output Regulation of Semilinear Infinite-Dimensional Systems (I) |
|
Vanspranghe, Nicolas | Tampere University |
Brivadis, Lucas | Université Paris-Saclay, CNRS, CentraleSupélec |
Paunonen, Lassi | Tampere University |
Keywords: Distributed parameter systems, Nonlinear systems, Lyapunov methods
Abstract: A stabilizer based on the forwarding technique is proposed for semilinear infinite-dimensional systems in cascade form. Sufficient conditions for local exponentially stability and global asymptotic stability of the closed-loop are derived. Results for the problem of local set-point output regulation are also obtained. Finally, an application to a system consisting of a flexible beam attached to a rotating joint is proposed.
|
|
17:00-17:20, Paper FrC06.4 | |
>Dual Parametric and State Estimation for Partial Differential Equations (I) |
|
Mowlavi, Saviz | MIT |
Benosman, Mouhacine | Mitsubishi Electric Research Laboratories |
Keywords: Fluid flow systems, Estimation, Kalman filtering
Abstract: Designing estimation algorithms for systems governed by partial differential equations (PDEs) such as fluid flows is challenging due to the high-dimensional and oftentimes nonlinear nature of the dynamics, as well as their dependence on unobserved physical parameters. In this paper, we propose two different lightweight and effective methodologies for realtime state estimation of PDEs in the presence of parametric uncertainties. Both approaches combines a Kalman filter with a data-driven polytopic linear reduced-order model obtained by dynamic mode decomposition (DMD). Using examples involving the nonlinear Burgers and Navier-Stokes equations, we demonstrate accurate estimation of both the state and the unknown physical parameter along system trajectories corresponding to various physical parameter values.
|
|
17:20-17:40, Paper FrC06.5 | |
>The Power Series Method to Compute Backstepping Kernel Gains: Theory and Practice (I) |
|
Vazquez, Rafael | Univ. De Sevilla |
Chen, Guangwei | Beijing University of Technology |
Qiao, Jun-fei | Beijing University of Technology |
Krstic, Miroslav | University of California, San Diego |
Keywords: Backstepping, Distributed parameter systems, Flexible structures
Abstract: Obtaining PDE backstepping controller or ob- server gains requires the solution of kernel PDEs - one or more hyperbolic PDEs on a triangular (Goursat) domain with non-standard boundary conditions. The numerical solution of these equations is a challenge that every designer applying backstepping must eventually face, except for the simplest of cases where explicit solutions are available. In addition, recent backstepping designs for coupled systems exhibit discontinuous behavior which must be accurately captured with the numerical approximation. In this paper, we propose a power series method as an alternative to other approaches. This method, which was introduced years ago in combination with convex optimization but whose convergence has only been recently formally established, offers several advantages, most of all simplicity, as it is quite easy to grasp and implement. Other features of the method include precision, adaptability to settings with discontinuous kernels, and the ability to produce symbolical kernels depending on parameters. The paper provides the necessary theoretical background, which borrows fundamental results from complex analysis and leverages already written kernel well-posedness proofs to show the existence of a power series solution. Links to the codes used in the simple examples are given; these are easily adaptable Mathematica notebooks. A complex multi-kernel, multiple-discontinuity example used in the stabilizing feedback law of a multilayer Timoshenko beam is given at the end, demonstrating the applicability of the method to some challenging families of kernel equations appearing in recent backstepping designs.
|
|
17:40-18:00, Paper FrC06.6 | |
>Computing Control Invariant Sets for Waiting-Time Switched Systems: A Study Case of Glucose Regulation |
|
Perez, Mara | CONICET-UNL |
Anderson, Alejandro | CONICET-INTEC-UNL |
Abuin, Pablo | CONICET-INTEC |
Hernandez-Vargas, Esteban Abelardo | University of Idaho |
González, Alejandro H. | CONICET-Universidad Nacional Del Litoral |
Actis, Marcelo | UNL-FIQ |
Keywords: Switched systems, Stability of hybrid systems, Biomedical
Abstract: Waiting-time constraints, bounding the minimum and maximum time of permanence in a given mode of a switched system, can be included in optimization-based control formulations by means of hard constraints. However, basic concepts such as equilibrium and invariance sets are modified by these constraints affecting the formal stability analysis as well. This paper explores general regions of the state space wherein switched system trajectories under waiting-time constraints can feasibly (and indefinitely) remain inside, replacing the concept of invariance with those of permanence. Explicit algorithms to compute these regions inside an (out of the origin) target window are provided, while the glucose regulation problem for Type 1 Diabetes Mellitus (T1DM) patients is considered as an example to highlight its main properties.
|
|
FrC07 |
Simpor Junior 4813 |
Game Theory VII |
Regular Session |
Chair: Caines, Peter E. | McGill University |
Co-Chair: Zhang, Renren | Shandong University |
|
16:00-16:20, Paper FrC07.1 | |
>On Logical Dynamic Potential Games (I) |
|
Jiang, Kaichen | Dalian University of Technology |
Li, Changxi | Peking University |
Guo, Lijuan | State Grid of China Technology College |
Wu, Yuhu | Dalian University of Technology |
Keywords: Boolean control networks and logic networks, Game theory, Optimal control
Abstract: Logical dynamic games are dynamic games with logical dynamics describing the external state evolutionary process, which exist widely in real systems like the Boolean network of lactose operon in Escherichia coli. To the best of our knowledge, there is little attention on LDGs. In this paper, we aim at developing a framework for the analysis of dynamic games with logical dynamics under finite-horizon criteria. First, mathematical model of logical dynamic games is provided. A necessary and sufficient condition for the existence of pure feedback Nash equilibrium in a logical dynamic game is derived. Second, rigorous mathematical model of logical dynamic potential game is proposed, which establishes the relationship between logical dynamic games and corresponding optimal control problems. Third, we proved that a logical dynamic game is a logical dynamic potential game, if and only if, all the static sub-games are potential games. Finally, an example is provided to illustrate the theoretical results.
|
|
16:20-16:40, Paper FrC07.2 | |
>Stabilizability of Game-Based Control Systems (I) |
|
Zhang, Renren | Shandong University |
Keywords: Game theory, Optimization, Hierarchical control
Abstract: We investigate the stabilizability of Nash equilibrium of the nonlinear game-based control system (GBCS), which has a similar decision-making structure as Stackelberg Games: one leader and multiple rational followers or agents. While the leader of the GBCS is a macro-regulator rather than a game player. The stabilizability problem is that whether the regulator can stabilize the system by regulating the Nash equilibrium formed by the agents at the lower level. The stabilizability of linear-quadratic GBCS has been investigated in cite{ZG_SCION_2021}. In this paper, we will first formulate the stabilizability problem of the general nonlinear GBCS. Then the stabilizability relationships between the linear-quadratic and nonlinear GBCSs are given, by investigating the solvable relationship of the associated algebraic Riccati equations and nonlinear Hamilton-Jacobi equations.
|
|
16:40-17:00, Paper FrC07.3 | |
>Can Mean Field Game Equilibria Amongst Exchangeable Agents Survive under Partial Observability of Their Competitors’ States? |
|
Rajabali, Farid | Polytechnique Montreal University |
Malhame, Roland P. | Ecole Poly. De Montreal |
Keywords: Mean field games, Stochastic optimal control, Communication networks
Abstract: Classical mean field games (MFG) have been concerned with large games amongst symmetrically influential agents with asymptotically negligible weight. In the absence of a common driving noise, propagation of chaos occurs. The analysis assumes that the initial agent's state probability distribution is known, making its future deterministic and computable via a fixed-point calculation under a limiting equilibrium policy, if it exists. However, oftentimes, despite equal mutual influence, a given agent can only observe a limited number of neighboring agents due to the agent observability structure characterized by an information access graph. This graph may have a low degree even with a large number of agents. The main question addressed is whether an MFG equilibrium can still potentially emerge asymptotically over time. The answer is affirmative, contingent on specific conditions that rely on the stability properties of agents' dynamics and the relative speed of communication to reactions, as derived in this study. The focus is on independent linear scalar agents correlated through a quadratic cost related to the mean state of the agents, which remains unobservable. To tackle convergence to a mean field equilibrium, the proposed model involves a fast communication time scale using a consensus algorithm, alongside a slower agent dynamic time scale. The research explores agents' ability to accurately estimate the system mean as both time and agent numbers increase.
|
|
17:00-17:20, Paper FrC07.4 | |
>Graphon Field Tracking Games with Discrete Time Q-Noise |
|
Dunyak, Alexander | McGill University |
Caines, Peter E. | McGill University |
Keywords: Mean field games, Stochastic optimal control, Stochastic systems
Abstract: Linear quadratic games on very large dense networks can be modelled with discrete time linear quadratic graphon field games with Q-noise. In such a game, each node in the graph corresponds to an agent weakly connected via an undirected network, with a correlated Brownian disturbance affecting each agent. The limit of the finite-sized linear quadratic network tracking game in discrete time is formulated, and it is shown that under the proper assumptions, the game has a graphon limit system with Q-noise. Then, the optimal control of the discrete time system is found in closed-form and the Nash equilibrium behavior of the game is numerically demonstrated.
|
|
17:20-17:40, Paper FrC07.5 | |
>A Game-Theoretic Approach for Optimal Dispatch of Building Thermal Loads Subject to Linear-Plus-Exponential Marginal Price |
|
Jiang, Zhimin | The University of Oklahoma |
Cai, Jie | University of Oklahoma |
Keywords: Building and facility automation, Game theory, Smart grid
Abstract: This paper introduces a game-theoretical strategy for optimal dispatch of building thermal loads, based on a marginal price model derived from an actual dispatch curve. A non-cooperative game is formulated, and the existence and uniqueness of the Nash equilibrium solution are proved aided by the variational inequality theory. A game solution algorithm is presented in this paper to solve the control problem with guaranteed convergence. The proposed game-theoretical control technique was evaluated against a baseline energy minimization strategy and a socially optimal solution, through a simulation test of a virtual market comprised of six buildings. The results show that the proposed game-theoretical strategy could achieve performance very close to the social optimum with a Price of Anarchy of 1.0041 and a 24% cost reduction compared to the baseline energy-priority strategy.
|
|
17:40-18:00, Paper FrC07.6 | |
>Optimal Orientation for Automated Vehicles on Large Lane-Free Roundabout (I) |
|
Naderi, Mehdi | Technical University of Crete |
Mavroeidi, Maria Konstantina | Technical University of Crete |
Papamichail, Ioannis | Technical University of Crete |
Papageorgiou, Markos | Technical Univ. of Crete |
Keywords: Autonomous vehicles, Optimal control, Automotive control
Abstract: Path planning for vehicles on large, complex, lane-free roundabouts is challenging due to the geometrical features and frequent conflicts among entering, navigating, and exiting vehicles. A key difficulty is to properly determine the desired vehicle orientations on the roundabout so that vehicles enter the roundabout and move towards their corresponding exits smoothly and safely. Specification of vehicle orientations should consider the resulting trip distance, the angle difference from other vehicles, and the exploitation of the available roundabout surface for efficient traffic flow. This paper proposes an optimal control approach to determine optimal vehicle orientations at each point on the roundabout, in dependence of the exit branch, so as to minimize a weighted sum of the trip distance and the deviation from the circular motion. Analytical solutions for two extreme cases, addressing only the shortest path or only the minimum deviation from the circular angle, respectively, are derived. For the general weighted problem solution, a Dynamic Programming-based (backward Dijkstra) algorithm is employed to deliver the optimal orientations in a 2-D space-discretized grid of the roundabout surface. In the light of the optimal solution, a computationally light near-optimal approach is also proposed. As a challenging case study, the methods are applied to the famous roundabout of Place Charles de Gaulle in Paris, which features a road width of 38 m and comprises 12 bidirectional radial streets, hence a total of 144 origin-destination movements for the vehicles.
|
|
FrC08 |
Simpor Junior 4812 |
Computational Methods |
Regular Session |
Chair: Ozer, Ahmet Ozkan | Western Kentucky University |
Co-Chair: Pohl, Volker | Technische Universität München |
|
16:00-16:20, Paper FrC08.1 | |
>Verification and Synthesis of Robust Control Barrier Functions: Multilevel Polynomial Optimization and Semidefinite Relaxation |
|
Kang, Shucheng | Harvard University |
Chen, Yuxiao | Nvidia Corporation |
Yang, Heng | Harvard University |
Pavone, Marco | Stanford University |
Keywords: Computational methods, Constrained control, LMIs
Abstract: We study the problem of verification and synthesis of robust control barrier functions (CBF) for control-affine polynomial systems with bounded additive uncertainty and convex polynomial constraints on the control. We first formulate robust CBF verification and synthesis as multilevel polynomial optimization problems (POP), where verification optimizes –in three levels– the uncertainty, control, and state, while synthesis additionally optimizes the parameter of a chosen parametric CBF candidate. We then show, by invoking the KKT conditions of the inner optimizations over uncertainty and control, the verification problem can be simplified as a single-level POP and the synthesis problem reduces to a min-max POP. This reduction leads to multilevel semidefinite relaxations. For the verification problem, we apply Lasserre’s hierarchy of moment relaxations. For the synthesis problem, we draw connections to existing relaxation techniques for robust min-max POP, which first uses sum-of-squares programming to find increasingly tight polynomial lower bounds to the unknown value function of the verification POP, and then call Lasserre’s hierarchy again to maximize the lower bounds. Both semidefinite relaxations guar- antee asymptotic global convergence to optimality. We provide an in-depth study of our framework on the controlled Van der Pol Oscillator, both with and without additive uncertainty.
|
|
16:20-16:40, Paper FrC08.2 | |
>Causal Discovery in Electronic Circuits and Its Application in Fault Diagnosis |
|
Rana, Mohammed Tuhin | University of Minnesota, Twin Cities, Minneapolis, MN |
Chakraborty, Soham | University of Minnesota |
Salapaka, Murti V. | University of Minnesota, Minneapolis |
Keywords: Computational methods, Fault diagnosis, Identification
Abstract: This article demonstrates that causal discovery approaches can be applied to analog electronic circuits made of Bipolar Junction Transistors (BJTs) to find out the causal relationships among different variables of the circuit. Moreover, the obtained causal relationship structure in the form of a Directed Acyclic Graph (DAG), can be used for diagnosis and analysis of such circuits. First, it is shown that the operation process of a transistor has an inherent notion of causality, which is then exploited to show that the various parameters of a BJT circuit can be expressed in the form of Structural Equation Models (SEM). The results demonstrated using data generated using LTspice establishes that the causal structure of a BJT circuit can be retrieved using data driven causal discovery algorithms. This opens new horizons for analysis and diagnosis of BJT circuits. An example case study of circuit diagnosis is presented to showcase the capability and efficiency of the proposed method.
|
|
16:40-17:00, Paper FrC08.3 | |
>The Wiener Theory of Causal Linear Prediction Is Not Effective |
|
Boche, Holger | Technische Universitaet Muenchen |
Pohl, Volker | Technische Universität München |
Poor, H. Vincent | Princeton Univ |
Keywords: Computational methods, Estimation, Stochastic systems
Abstract: In this paper, it will be shown that the minimum mean square error (MMSE) for predicting a stationary stochastic time series from its past observations is not generally Turing computable, even if the spectral density of the stochastic process is differentiable with a computable first derivative. This implies that for any approximation sequence that converges to the MMSE there does not exist an algorithmic stopping criterion that guarantees that the computed approximation is sufficiently close to the true value of the MMSE. Furthermore, it will be shown that under the same conditions on the spectral density, it is also the case that coefficients of the optimal prediction filter are not generally Turing computable.
|
|
17:00-17:20, Paper FrC08.4 | |
>Time and Memory-Efficient Computation of Hamilton-Jacobi Reachable Sets Based on a Level Set Method Employing Adaptive Grids |
|
Bohn, Christopher | Karlsruhe Institute of Technology (KIT) |
Reis, Philipp | Forschungszentrum Informatik |
Schwartz, Manuel | Karlsruhe Institute of Technology |
Hohmann, Soeren | KIT |
Keywords: Computational methods, Formal Verification/Synthesis, Control applications
Abstract: Formal verification of dynamic control systems often involves reachability analysis to ensure safety and performance characteristics. Hereby, Hamilton-Jacobi-based methods are beneficial as they can be applied to non-linear, continuous systems under the influence of bounded disturbances. Furthermore, they can consider input- and state constraints. These benefits come with the computational effort of solving a Hamilton-Jacobi partial differential equation. State-of-the-art methods numerically determine a viscosity solution at the vertices of a static grid that is used to discretize the state space. This becomes particularly costly if the reachable set propagates fast and needs to be determined precisely, as this requires a grid of many vertices. This contribution proposes a method that computes the solution successively on small adaptive grids instead of on one static grid to reduce the computational effort of Hamilton-Jacobi reachability analysis. Using the proposed method, changes between grids can be performed in an outer or inner approximative manner. The performance of the proposed method is demonstrated in a numerical example computing a forward reachable set of a Dubins car model. While increasing the accuracy of the resulting set, the method proposed saves 73 % of computation time, 76 % of average memory usage, and 43 % of maximum memory usage in the presented scenario.
|
|
17:20-17:40, Paper FrC08.5 | |
>A Novel Finite Difference-Based Model Reduction and a Sensor Design for a Multilayer Smart Beam with Arbitrary Number of Layers |
|
Aydin, Ahmet Kaan | University of Maryland, Baltimore County |
Ozer, Ahmet Ozkan | Western Kentucky University |
Walterman, Jacob | Western Kentucky University |
Keywords: Computational methods, Numerical algorithms, Smart structures
Abstract: A Mead-Marcus type model describing the vibrations on a multilayer smart beam with arbitrary number of layers is considered with hinged boundary conditions. The model is known to be exactly observable in an appropriate Hilbert space with a single boundary sensor measurement. As a standard Finite Differences-based model reduction is considered, it is proved that the model reduction lacks exact observability uniformly as the mesh parameter goes to zero. This is a known phenomenon caused by spurious (artificial) high-frequency eigenvalues. First, it is proved that the exact observability can be retained by the implementation of the direct Fourier filtering technique. However, the optimality of the applied filtering demands further investigation. For this reason, an alternate model reduction is investigated by cleverly reducing the order of the model together with the consideration of equidistant grid points and averaging operators, as in Liu and Guo (2019, 2020, and 2021). This new model reduction successfully retains the exact observability uniformly as as the mesh parameter goes to zero. Moreover, it does not need a further numerical filtering. Our results are based on carefully analyzing the spectrum of the system matrix, and they are applicable to the standard Euler-Bernoulli and Rayleigh beam equations. The numerical simulations are provided to compare reduced models and to show the strength of introduced results.
|
|
17:40-18:00, Paper FrC08.6 | |
>General Extremal Field Method for Time-Optimal Trajectory Planning in Flow Fields |
|
Schnitzler, Bastien | ISAE-SUPAERO |
Drouin, Antoine | ENAC (French Civil Aviation Institute) |
Moschetta, Jean-Marc | Institut Superieur De l'Aeronautique Et De L'Espace |
Delahaye, Daniel | École Nationale De l'Aviation Civile |
Keywords: Computational methods, Optimal control, Autonomous vehicles
Abstract: We present an algorithm to compute time-optimal trajectories for light vehicles in unsteady flow fields, with applications to long-range, low-power aircraft as well as underwater vehicles in ocean currents. The proposed approach aims at unifying various works from the literature on extremal fields and extends it by several features. First, we propose an exact scheme to deal with still obstacles. While being directly useful for pure obstacles, it is also of particular interest to ensure the validity of computation at the borders of the problem domain. Second, we demonstrate the method ability to deal with trajectory planning for long-range airborne missions with real weather data. Lastly, the source code, written in Python, is made open to the community to accelerate research in the domain.
|
|
FrC09 |
Simpor Junior 4811 |
Optimization IV |
Regular Session |
Chair: Schenato, Luca | University of Padova |
Co-Chair: Tzoumas, Vasileios | University of Michigan, Ann Arbor |
|
16:00-16:20, Paper FrC09.1 | |
>A Spectral Bundle Method for Sparse Semidefinite Programs |
|
Mojtahedi, Hesam | University of California San Diego |
Liao, Feng-Yi | University of California San Diego |
Zheng, Yang | University of California San Diego |
Keywords: Optimization, Optimization algorithms
Abstract: Semidefinite programs (SDPs) have many applications in the field of controls. To improve~scalability, it is important to exploit the inherent sparsity when solving SDPs. In this paper, we develop a new spectral bundle algorithm that solves sparse SDPs without introducing additional variables. We first apply chordal decomposition to replace a large positive semidefinite (PSD) constraint with a set of smaller coupled constraints. Then, we move the coupled constraints into the cost function via exact penalty. This leads to an equivalent non-smooth penalized problem, which can be solved by bundle methods. We present a new efficient spectral bundle algorithm, where subgradient information is incorporated to update a lower approximation at each iteration. We further establish sublinear convergences in terms of objective value, primal feasibility, dual feasibility, and duality gap. Under Slater's condition, the algorithm converges with the rate of bigOleft (1/epsilon^3 right), and the rate improves to bigO left (1/epsilon right) when strict complementarity holds. Our numerical experiments support the theoretical analysis.
|
|
16:20-16:40, Paper FrC09.2 | |
>React to the Worst: Efficient and Proactive Protection of Location Privacy |
|
Molina, Emilio | Univ. Grenoble Alpes, CNRS, Grenoble INP, |
Fiacchini, Mirko | CNRS, Univ. Grenoble Alpes |
Cerf, Sophie | Inria Université De Lille |
Robu, Bogdan | Grenoble Alpes University, GIPSA-Lab |
Keywords: Optimization, Predictive control for linear systems, Emerging control applications
Abstract: This work presents a novel optimal control method for privacy protection of mobility data. %, based on worst-case anticipation. Protection is based on data obfuscation, consisting in sending to the geolocated service a finely tuned fake location. The objective is twofold, keeping privacy values at an acceptable level and guaranteeing a reasonable utility loss, with a lightweight algorithm able to run on mobile devices. The proposed method consists of an offline modeling stage, based on privacy worst-case anticipation, and a fast algorithm executed online. In the offline stage, the algorithm computes the average amount of allowed utility loss necessary to maintain the privacy value of the following h steps above a given lower bound. For this purpose, the worst possible scenario over the future steps is computed and compared with the privacy function of the solution obtained by an MPC method. The online stage uses the information computed offline to solve an optimization problem whose decision variable is the location to transmit and whose objective is to maintain the privacy value above a minimal level, by avoiding large utility losses. The method is validated on an instance of a database of real records and compared with a state-of-the-art competitor.
|
|
16:40-17:00, Paper FrC09.3 | |
>Efficient Online Learning with Memory Via Frank-Wolfe Optimization: Algorithms with Bounded Dynamic Regret and Applications to Control |
|
Zhou, Hongyu | University of Michigan |
Xu, Zirui | University of Michigan |
Tzoumas, Vasileios | University of Michigan, Ann Arbor |
Keywords: Optimization, Time-varying systems
Abstract: Projection operations are a typical computation bottleneck in online learning. In this paper, we enable projection-free online learning within the framework of Online Convex Optimization with Memory (OCO-M) ---OCO-M captures how the history of decisions affects the current outcome by allowing the online learning loss functions to depend on both current and past decisions. Particularly, we introduce the first projection-free meta-base learning algorithm with memory that minimizes dynamic regret, i.e., that minimizes the suboptimality against any sequence of time-varying decisions. We are motivated by applications where autonomous agents need to adapt to time-varying environments in real-time, accounting for how past decisions affect the present. Examples of such applications are: online control of dynamical systems; statistical arbitrage; and time series prediction. The algorithm builds on the Online Frank-Wolfe (OFW) and Hedge algorithms. We demonstrate how our algorithm can be applied to the online control of linear time-varying systems in the presence of unpredictable process noise. To this end, we develop the first controller with memory and bounded dynamic regret against any optimal time-varying linear feedback control policy.
|
|
17:00-17:20, Paper FrC09.4 | |
>Comparing Structured Ambiguity Sets for Stochastic Optimization: Application to Uncertainty Quantification |
|
Chaouach, Lotfi Mustapha | TU Delft |
Oomen, Tom | Eindhoven University of Technology |
Boskos, Dimitris | TU Delft |
Keywords: Optimization, Uncertain systems, Stochastic systems
Abstract: The aim of this paper is to compare two classes of structured ambiguity sets, which are data-driven and can reduce the conservativeness of their associated optimization problems. These two classes of structured sets, coined Wasserstein hyperrectangles and multi-transport hyperrectangles, are explored in their trade-offs in terms of reducing conservativeness and providing tractable reformulations. It follows that multi-transport hyperrectangles lead to tractable optimization problems for a significantly broader range of objective functions under a decent compromise in terms of conservativeness reduction. The results are illustrated in an uncertainty quantification case study.
|
|
17:20-17:40, Paper FrC09.5 | |
>Data-Driven Stochastic Optimization Using Upper Confidence Bounds: Performance Guarantees and Distributional Robustness |
|
Cho, Youngchae | Seoul National University |
Yang, Insoon | Seoul National University |
Keywords: Optimization
Abstract: A data-driven approach for stochastic optimization should preferably offer a finite-sample performance guarantee as well as asymptotic optimality. However, existing approaches that enjoy both, mostly based on distributionally robust optimization (DRO), are often difficult to use as they require an ambiguity set containing the true distribution of uncertainty with confidence, which is difficult to obtain. The main contributions of this paper are two-fold. First, we propose a data-driven stochastic optimization approach that offers a finite-sample guarantee and asymptotic optimality without resorting to an ambiguity set. The core idea of our approach is to minimize an approximation to the true expected cost function derived using only a half of the sample data, and compute an upper confidence bound for the true expected cost using the other half. Second, we identify a case in which the proposed approach is tractable and accordingly design an algorithm for it. Simulation results demonstrate that our approach can be less conservative than existing DRO methods in terms of not only the finite-sample guarantee but also the true expected cost for a wide range of frequently used confidence levels.
|
|
17:40-18:00, Paper FrC09.6 | |
>ZO-JADE: Zeroth-Order Curvature-Aware Distributed Multi-Agent Convex Optimization |
|
Maritan, Alessio | Università Degli Studi Di Padova |
Schenato, Luca | University of Padova |
Keywords: Optimization, Networked control systems, Distributed control
Abstract: In this work we address the problem of convex optimization in a multi-agent setting where the objective is to minimize the sum of local cost functions whose derivatives are not available (black box models). Moreover agents can only communicate with local neighbors according to a connected network topology. Zeroth-order (ZO) optimization has recently gained increasing attention in federated learning and multi-agent scenarios exploiting finite-difference approximations of the gradient using from 2 (directional gradient) to 2d (central difference full gradient) evaluations of the cost functions, where d is the dimensionality of the problem. The contribution of this work is to extend ZO distributed optimization by estimating the curvatures/Hessian of the local cost functions via finite difference approximations. In particular, we propose a novel algorithm, named ZO-JADE, that by adding just one extra point, i.e. 2d+1 in total, allows to simultaneously estimate the gradient and the diagonal of the local Hessian, which is then combined via average tracking consensus algorithms to obtain an approximated Jacobi descent. Guarantees of semi-global exponential stability are established via separation of time-scales and extensive numerical experiments on real-world data confirmed the efficiency and superiority with respect to several other distributed zeroth-order methods available in the literature based on only gradient estimates.
|
|
FrC10 |
Roselle Junior 4713 |
Learning II |
Regular Session |
Chair: Diddigi, Raghuram Bharadwaj | International Institute of Information Technology, Bangalore |
Co-Chair: Zhu, Quanyan | New York University |
|
16:00-16:20, Paper FrC10.1 | |
>Emulation Learning for Neuromimetic Systems |
|
Sun, Zexin | Boston University |
Baillieul, John | Boston Univ |
Keywords: Learning, Quantized systems, Resilient Control Systems
Abstract: Building on our recent research on neural heuristic quantization systems, results on learning quantized motions and resilience to channel dropouts are reported. We propose a general emulation problem consistent with the neuromimetic paradigm. This optimal quantization problem can be solved by model predictive control (MPC), but because the optimization step involves integer programming, the approach suffers from combinatorial complexity when the number of input channels becomes large. Even if we collect data points to train a neural network simultaneously, collection of training data and the training itself are still time-consuming. Therefore, we propose a general Deep Q Network (DQN) algorithm that can not only learn the trajectory but also exhibit the advantages of resilience to channel dropout. Furthermore, to transfer the model to other emulation problems, a mapping-based transfer learning approach can be used directly on the current model to obtain the optimal direction for the new emulation problems.
|
|
16:20-16:40, Paper FrC10.2 | |
>BiRP: Learning Robot Generalized Bimanual Coordination Using Relative Parameterization Method on Human Demonstration |
|
Liu, Junjia | The Chinese University of Hong Kong |
Sim, Hengyi | The Chinese University of Hong Kong |
Li, Chenzui | The Chinese University of Hong Kong |
Tan, Kay Chen | The National Univ. of Singapore |
Chen, Fei | The Chinese University of Hong Kong |
Keywords: Learning, Robotics
Abstract: Human bimanual manipulation can perform more complex tasks than a simple combination of two single arms, which is credited to the spatio-temporal coordination between the arms. However, the description of bimanual coordination is still an open topic in robotics. This makes it difficult to give an explainable coordination paradigm, let alone applied to robotics. In this work, we divide the main bimanual tasks in human daily activities into two types: leader-follower and synergistic coordination. Then we propose a relative parameterization method to learn these types of coordination from human demonstration. It represents coordination as Gaussian mixture models from bimanual demonstration to describe the change in the importance of coordination throughout the motions by probability. The learned coordinated representation can be generalized to new task parameters while ensuring spatio-temporal coordination. We demonstrate the method using synthetic motions and human demonstration data and deploy it to a humanoid robot to perform a generalized bimanual coordination motion. We believe that this easy-to-use bimanual learning from demonstration (LfD) method has the potential to be used as a data augmentation plugin for robot large manipulation model training. The corresponding codes are open-sourced in https://github.com/Skylark0924/Rofunc.
|
|
16:40-17:00, Paper FrC10.3 | |
>Physics-Model-Regulated Deep Reinforcement Learning towards Safety & Stability Guarantees |
|
Cao, Hongpeng | Technical University of Munich |
Mao, Yanbing | Wayne State University |
Sha, Lui | University of Illinois at Urbana Champaign |
Caccamo, Marco | Technical University of Munich |
Keywords: Learning, Robust control, Lyapunov methods
Abstract: Deep reinforcement learning (DRL) has demonstrated impressive success in solving complex control tasks by synthesizing control policies from data. However, the safety and stability of applying DRL to safety-critical systems remain a primary concern and challenging problem. To address the problem, we propose the Phy-DRL: a novel physics-model-regulated deep reinforcement learning framework. The Phy-DRL is novel in two architectural designs: a physics-model-regulated reward and residual control, which integrates physics-model-based control and data-driven control. The concurrent designs enable the Phy-DRL the mathematically provable safety and stability guarantees. Finally, the effectiveness of the Phy-DRL is validated by an inverted pendulum system. Additionally, the experimental results demonstrate that the Phy-DRL features remarkably accelerated training and enlarged reward.
|
|
17:00-17:20, Paper FrC10.4 | |
>Efficient Off-Policy Algorithms for Structured Markov Decision Processes |
|
Ganguly, Sourav | IIT Dharwad |
Diddigi, Raghuram Bharadwaj | International Institute of Information Technology, Bangalore |
K.J., Prabuchandran | Indian Institute of Technology, Dharwad |
Keywords: Learning, Stochastic optimal control, Neural networks
Abstract: Reinforcement Learning (RL) algorithms help in training an autonomous agent to learn the optimal actions in an unknown environment. RL, in conjunction with neural networks, known as deep RL, has achieved remarkable success in many real-life practical applications. However, most of these algorithms are complex to train and require a lot of data to learn optimal decisions. Hence, it is imperative to develop RL algorithms that are simple and data efficient. In this work, we propose off-policy RL algorithms that can exploit special structures present in the optimal policy of the underlying Markov Decision process. The off-policy learning enables us to make use of the available data efficiently. To this end, we first propose an off-policy algorithm that estimates the value function of only those policies with the optimal policy structure to determine the best policy. We then propose two novel off-policy algorithms utilizing Upper Confidence Bound (UCB) with less time and space complexity than our first algorithm. Through extensive experimental evaluations on RL benchmark tasks, we illustrate the efficacy of the proposed algorithms.
|
|
17:20-17:40, Paper FrC10.5 | |
>Online Adversarial Stabilization of Unknown Linear Time-Varying Systems |
|
Yu, Jing | California Institute of Technology |
Gupta, Varun | University of Chicago |
Wierman, Adam | California Institute of Technology |
Keywords: Learning, Time-varying systems, Data driven control
Abstract: This paper studies the problem of online stabilization of an unknown discrete-time linear time-varying (LTV) system under bounded non-stochastic (potentially adversarial) disturbances. We propose a novel algorithm based on convex body chasing (CBC). Under the assumption of infrequently changing or slowly drifting dynamics, the algorithm guarantees bounded-input-bounded-output stability in the closed loop. Our approach avoids system identification and applies, with minimal disturbance assumptions, to a variety of LTV systems of practical importance. We demonstrate the algorithm numerically on examples of LTV systems including Markov linear jump systems with finitely many jumps.
|
|
17:40-18:00, Paper FrC10.6 | |
>Is Stochastic Mirror Descent Vulnerable to Adversarial Delay Attacks? a Traffic Assignment Resilience Study |
|
Pan, Yunian | New York University |
Li, Tao | New York University |
Zhu, Quanyan | New York University |
Keywords: Learning, Transportation networks, Cyber-Physical Security
Abstract: Intelligent Navigation Systems (INS) are exposed to an increasing number of informational attack vectors, which often intercept through the communication channels between the INS and the transportation network during the data-collecting process. To measure the resilience of INS, we use the concept of a Wardrop Non-Equilibrium Solution (WANES), which is characterized by the probabilistic outcome of learning within a bounded number of interactions. By using concentration arguments, we have discovered that any bounded feedback delaying attack only degrades the systematic performance up to order tilde{mathcal{O}}(sqrt{{d^3}{T^{-1}}}) along the traffic flow trajectory within the Delayed Mirror Descent (DMD) online-learning framework. This degradation in performance can occur with only mild assumptions imposed. Our result implies that learning-based INS infrastructures can achieve Wardrop Non-equilibrium even when experiencing a certain period of disruption in the information structure. These findings provide valuable insights for designing defense mechanisms against possible jamming attacks across different layers of the transportation ecosystem.
|
|
FrC11 |
Roselle Junior 4712 |
Large-Scale Systems III |
Regular Session |
Chair: Xiang, Cheng | National University of Singapore |
Co-Chair: Datta, Subashish | Indian Institute of Technology Delhi |
|
16:00-16:20, Paper FrC11.1 | |
>New Results on Input-Output Decoupling of Boolean Control Networks (I) |
|
Li, Yiliang | Shandong University |
Lyu, Hongli | Lakehead University |
Feng, Jun-e | Shandong University |
Tayebi, Abdelhamid | Lakehead University |
Keywords: Boolean control networks and logic networks
Abstract: We provide new necessary and sufficient conditions (with low computational complexity) for the input-output decoupling problem of Boolean control networks. Instrumental in our approach, the introduction of a new concept relying on the construction of some input-output-decoupling matrices that have to satisfy some conditions to ascertain whether a given Boolean control network is input-output decoupled. A numerical example is provided to illustrate our theoretical developments.
|
|
16:20-16:40, Paper FrC11.2 | |
>Synchronous of Multiagent Systems Over Finite Fields Via Event-Triggered Control |
|
Yu, Miao | Liaocheng University |
Xia, Jianwei | Liaocheng University |
Feng, Jun-e | Shandong University |
Fu, Shihua | Liaocheng University |
Keywords: Boolean control networks and logic networks
Abstract: This paper studies the leader-follower syn- chronous of multiagent systems (MASs) over finite fields by the event-triggered control (ETC). First, the MASs over finite fields with ETC are modeled as algebraic form by the semi-tensor product (STP) method, based on which, the event-triggered synchronous problem is transformed into the set stabilization problem about the system with algebraic form. Secondly, the maximum invariant set is selected as the target set to reduce the number of controller execution times. Thirdly, the necessary and sufficient conditions of the event-triggered synchronous of the MAS as well as the design method of the optimal state feedback event-triggered controller are given. Finally, an example is presented to illustrate the conclusion of this paper.
|
|
16:40-17:00, Paper FrC11.3 | |
>Robust Set Stabilization of Boolean Control Networks: An Efficient Approach Based on Reverse Set Propagation |
|
Gao, Shuhua | Shandong University |
Wang, Qian | Shandong Huate Magnet Technology Co., Ltd |
Li, Yakun | Shandong University |
Li, Zezheng | Shandong University |
Xiang, Cheng | National University of Singapore |
Keywords: Boolean control networks and logic networks, Optimal control, Robust control
Abstract: This paper investigates the robust set stabilization of nondeterministic Boolean control networks (BCNs) subject to random disturbance inputs. Although this problem has been previously addressed in the literature, we propose an alternative approach primarily to decrease the computational complexity of the algorithms. Our technique is inspired by the set propagation technique in reachability analysis but is applied in reverse order, identifying all the layered sets of states that reach a target set in a specific order. Two algorithms are developed: the first determines the largest robust control invariant subset, while the second handles time-optimal robust set stabilization using the results from the first algorithm. In particular, all time-invariant state feedback gain matrices are identified. Our approach achieves the lowest computational complexity ever known, even lower than the current methods designed solely for deterministic set stabilization without any disturbances. Numerical simulations with two biological networks demonstrate the significantly reduced processing time of our algorithms. Overall, this study presents a new approach for robust set stabilization with improved efficiency, capable of handling relatively large BCNs beyond the capabilities of existing techniques.
|
|
17:00-17:20, Paper FrC11.4 | |
>Impulse Elimination and Synchronization in Descriptor Multi-Agent Systems |
|
Patel, Meera | IIT Delhi |
Datta, Subashish | Indian Institute of Technology Delhi |
Keywords: Differential-algebraic systems, Cooperative control, Distributed control
Abstract: In this work, a control methodology is proposed to address the problems of impulse elimination and leader-follower state synchronization in a descriptor multi-agent system (DMAS), where each agent in the network is a descriptor system. A distributed static state feedback control protocol is proposed to achieve the control objectives. By making the closed loop DMAS impulse-free through a feedback gain matrix, it is transformed into a set of decoupled descriptor systems using the property of network graph Laplacian matrix, and then, the synchronization problem is transformed into stabilization problem of a set of ordinary state space systems. Since we have used only orthogonal matrices for system transformations, the proposed algorithm is numerically efficient. The effectiveness of the proposed methodology is demonstrated with an example.
|
|
17:20-17:40, Paper FrC11.5 | |
>Multi-Agent Distributed and Decentralized Geometric Task Allocation |
|
Amir, Michael | Technion - Israel Institute of Technology |
Koifman, Yigal | Technion - Israel Institute of Technology |
Bloch, Yakov | Bar-Ilan University |
Barel, Ariel | Technion - Israel Institute of Technology |
Bruckstein, Alfred | Technion |
Keywords: Agents-based systems, Autonomous robots, Adaptive control
Abstract: We consider the general problem of geometric task allocation, wherein a large, decentralized swarm of simple mobile agents must detect the locations of tasks in the plane and position themselves nearby. The tasks are represented by an a priori unknown demand profile Φ(x,y) that determines how many agents are needed in each location. The agents are autonomous, oblivious, indistinguishable, and have a finite sensing range. They must configure themselves according to Φ using only local information about Φ and about the positions of nearby agents. All agents act according to the same local sensing-based rule of motion, and cannot explicitly communicate nor share information. We propose an approach based on gradient descent over a simple squared error function. We formally show that this approach results in attraction-repulsion dynamics. Repulsion encourages agents to spread out and explore the region to find the tasks, and attraction causes them to accumulate at task locations. The figures in this work are snapshots of simulations that can be viewed at https://youtu.be/1_5f0MnUJag.
|
|
17:40-18:00, Paper FrC11.6 | |
>Distributed Model Predictive Controller for Thermal Energy Management System of Battery Electric Vehicles |
|
Lokur, Prashant | Chalmers University of Technology |
Murgovski, Nikolce | Chalmers University of Technology |
Nicklasson, Kristian | CEVT |
Keywords: Automotive control, Distributed control, Control applications
Abstract: This paper proposes a distributed model predictive controller (DMPC) that utilizes the alternating direction method of multipliers for the thermal energy management system of a battery electric vehicle. The system comprises a heating, ventilation, and air conditioning unit along with a heat pump. Comparison of the optimal results from a centralized model predictive controller (MPC) and DMPC with those obtained through a rule-based strategy indicate that both the centralized MPC and DMPC deliver energy savings of SI{9.85}{percent} and SI{2.21}{percent}, respectively.
|
|
FrC12 |
Roselle Junior 4711 |
Distributed Control III |
Regular Session |
Chair: Fujisaki, Yasumasa | Osaka Univ |
Co-Chair: Parasnis, Rohit | Purdue University |
|
16:00-16:20, Paper FrC12.1 | |
>Fast Decentralized Multi-Agent Collision Avoidance Based on Safe-Reachable Sets |
|
Ouyang, Zikai | Southern University of Science and Technology |
Liu, Junwei | Southern University of Science and Technology |
Lu, Haibo | Peng Cheng Laboratory |
Zhang, Wei | Southern University of Science and Technology |
Keywords: Distributed control, Optimization algorithms, Autonomous systems
Abstract: This paper presents a decentralized multi-agent collision avoidance method for systems with single integrator dynamics and identical maximum speeds. The key to our approach lies in the concept of safe-reachable sets, which define the set of positions that each agent can reach while avoiding collisions with its neighbors for any admissible controllers. With this concept, we develop a distributed controller by solving an online convex program, which is shown to guarantee collision-free trajectories. Furthermore, under a no temporary deadlock condition, we establish that each agent converges to its target position. Our approach is also efficient in terms of makespan, representing the total time needed for convergence. Simulation results demonstrate the effectiveness of our approach in terms of safety, convergence, and efficiency.
|
|
16:20-16:40, Paper FrC12.2 | |
>ALADIN-Based Distributed Model Predictive Control with Dynamic Partitioning: An Application to Solar Parabolic Trough Plants |
|
Chanfreut, Paula | Eindhoven University of Technology |
Maestre, Jose Maria (Pepe) | University of Seville |
Krishnamoorthy, Dinesh | TU Eindhoven |
Camacho, Eduardo F. | Univ. of Sevilla |
Keywords: Distributed control, Predictive control for nonlinear systems, Cooperative control
Abstract: This article presents a distributed model predictive controller with time-varying partitioning based on the augmented Lagrangian alternating direction inexact Newton method (ALADIN). In particular, we address the problem of controlling the temperature of a heat transfer fluid (HTF) in a set of loops of solar parabolic collectors by adjusting its flow rate. The control problem involves a nonlinear prediction model, decoupled inequality constraints, and coupled affine constraints on the system inputs. The application of ALADIN to address such a problem is combined with a dynamic clustering-based partitioning approach that aims at reducing, with minimum performance losses, the number of variables to be coordinated. Numerical results on a 10-loop plant are presented.
|
|
16:40-17:00, Paper FrC12.3 | |
>Signal Comparison Average Consensus Algorithm under Binary-Valued Communications |
|
Ke, Jieming | Academy of Mathematics and Systems Science, Chinese Academy of S |
Zhao, Yanlong | Academy of Mathematics and Systems Science, Chinese Academyof Sci |
Zhang, Ji-Feng | Chinese Academy of Sciences |
Keywords: Distributed control, Quantized systems, Stochastic systems
Abstract: The average consensus problem under binary-valued communications is investigated in the paper. Measurement noises and fixed quantizers are considered. A signal comparison algorithm is proposed for the problem. Neither the noise distribution information nor assumptions on the states’ approximate locations are required for the algorithm design. The signal comparison algorithm is proved to achieve average consensus both in the almost sure and mean square sense. The algorithm’s mean square convergence rate is also calculated. The efficiency of the algorithm is demonstrated by a numerical example.
|
|
17:00-17:20, Paper FrC12.4 | |
>Leader-Follower Formation of Second-Order Agents Via Delayed Relative Displacement Feedback |
|
Lizzio, Fausto Francesco | Politecnico Di Torino |
Capello, Elisa | Politecnico Di Torino, CNR-IEIIT |
Fujisaki, Yasumasa | Osaka Univ |
Keywords: Distributed control, Stability of linear systems, Delay systems
Abstract: This paper investigates a leader-follower formation of a group of second-order agents, considering an undirected and connected topology. It is assumed that no velocity information is available, and that a uniform delay affects the processing of the displacement information. To address these issues, a delayed relative displacement feedback is introduced. A necessary and sufficient condition for stability is derived in terms of a delay threshold, given that the delay-free controller is stable. Moreover, a stability region in the complex plane for the eigenvalues of the Laplacian interaction matrix is introduced. The results are illustrated through numerical examples.
|
|
17:20-17:40, Paper FrC12.5 | |
>On the Effects of Data Heterogeneity on the Convergence Rates of Distributed Linear System Solvers |
|
Velasevic, Boris | Massachusetts Institute of Technology |
Parasnis, Rohit | Purdue University |
Brinton, Christopher | Purdue University |
Azizan, Navid | MIT |
Keywords: Computational methods, Optimization algorithms, Distributed control
Abstract: We consider the fundamental problem of solving a large-scale system of linear equations over a number of machines in a federated manner, i.e., where a taskmaster intends to solve the system with the help of a set of machines, who each have a subset of the equations. Although there exist several approaches for solving this problem, missing is a rigorous comparison between the convergence rates of the projection-based methods and those of the optimization-based ones. In this paper, we analyze and compare these two classes of algorithms with a particular focus on the most efficient method from each class, namely, the recently proposed Accelerated Projected Consensus (APC) and the Distributed Heavy-Ball Method (D-HBM). To this end, we first propose a geometric notion of data heterogeneity called angular heterogeneity and discuss its generality. Using this notion, we bound and compare the convergence rates of the studied algorithms and capture the effects of both cross-machine and local data heterogeneity on these quantities. Our analysis results in a number of novel insights besides showing that APC is the most efficient method in realistic scenarios where there is a large data heterogeneity. Our numerical analyses validate our theoretical results.
|
|
17:40-18:00, Paper FrC12.6 | |
>Value Iteration Algorithm for Solving Shortest Path Problems with Homology Class Constraints |
|
He, Wenbo | Washington University in St. Louis |
Huang, Yunshen | Washington University in St. Louis |
Qie, Jinran | Washington University in St. Louis |
Zeng, Shen | Washington University in St. Louis |
Keywords: Computational methods, Optimization algorithms
Abstract: Path planning is a fundamental problem in robotics that aims to find an optimal path for a system to move on while avoiding obstacles in the environment. Often, a feasible path connecting the start and target point with the shortest length is highly desirable. Additionally, in scenarios such as drone racing or surveillance, topology constraints may arise. In this paper, we propose a novel method to address the shortest path problem with homology class constraints in both 2D and 3D environments. We first define the phase change of the path with respect to 2D obstacles and then apply the same technique to a class of super-toroid obstacles compressed by an embedding map. To synthesize the shortest path, we leverage the visibility graph and the Value Iteration Algorithm (VIA). Finally, we demonstrate the effectiveness of our approach with various simulation examples.
|
|
FrC13 |
Roselle Junior 4613 |
Sensor Networks |
Regular Session |
Chair: Aghdam, Amir G. | Concordia University |
Co-Chair: Guay, Martin | Queens University |
|
16:00-16:20, Paper FrC13.1 | |
>Jointly Observable State Estimation for Linear Systems Over Periodic Time-Varying Networks |
|
Wang, Shimin | Queen's University |
Guay, Martin | Queens University |
Keywords: Sensor networks, Agents-based systems, Large-scale systems
Abstract: This paper deals with the distributed state estimation problem for jointly observable multi-agent systems operated over network with time-varying topologies. The approach is shown to extend the design of distributed observers to unstable observable systems on communication networks with intermittent connection losses. This includes the connected static networks as well as every-time connected switching networks as special cases. Sufficient conditions for the existence of distributed observers for general linear observable systems over periodic communication networks are presented. A toy numerical example and a practical application are provided to illustrate the effectiveness of the theoretical results.
|
|
16:20-16:40, Paper FrC13.2 | |
>Accelerated Multi-Stage Discrete Time Dynamic Average Consensus |
|
Sebastián, Eduardo | Universidad De Zaragoza |
Montijano, Eduardo | Universidad De Zaragoza |
Sagues, Carlos | Universidad De Zaragoza |
Franceschelli, Mauro | University of Cagliari |
Gasparri, Andrea | Roma Tre University |
Keywords: Sensor networks, Distributed control, Estimation
Abstract: This paper presents a novel solution for the discrete time dynamic average consensus problem. Given a set of time-varying input signals over the nodes of an undirected graph, the proposed algorithm tracks, at each node, the input signals' average. The algorithm is based on a sequence of consensus stages combined with a second order diffusive protocol. The former overcomes the need of k-th order differences of the inputs and conservation of the network state average, while the latter overcomes the trade-off between speed and accuracy of the consensus stages by just storing the previous estimate at each node. The result is a protocol that is fast, arbitrarily accurate, and robust against input noises and initializations. The protocol is extended to an asynchronous and randomized version that follows a gossiping scheme that is robust against potential delays and packet losses. We study the convergence properties of the algorithms and validate them via simulations.
|
|
16:40-17:00, Paper FrC13.3 | |
>State-Robust Observability Measures for Sensor Selection in Nonlinear Dynamic Systems |
|
Kazma, Mohamad | Vanderbilt University |
Nugroho, Sebastian Adi | Cummins Inc |
Haber, Aleksandar | City University of New York |
Taha, Ahmad | Vanderbilt University |
Keywords: Sensor networks, Nonlinear systems, Observers for nonlinear systems
Abstract: This paper explores the problem of selecting sensor nodes for a general class of nonlinear dynamical networks. In particular, we study the problem by utilizing altered definitions of observability and open-loop lifted observers. The approach is performed by discretizing the system's dynamics using the implicit Runge-Kutta method and by introducing a state-averaged observability measure. The observability measure is computed for a number of perturbed initial states in the vicinity of the system's true initial state. The sensor node selection problem is revealed to retain the submodular and modular properties of the original problem. This allows the problem to be solved efficiently using a greedy algorithm with a guaranteed performance bound while showing an augmented robustness to unknown or uncertain initial conditions. The validity of this approach is numerically demonstrated on a H_{2}/O_{2} combustion reaction network.
|
|
17:00-17:20, Paper FrC13.4 | |
>A Distributed Strategy to Maximize Coverage in a Heterogeneous Sensor Network in the Presence of Obstacles |
|
Mosalli, Hesam | Concordia University |
Aghdam, Amir G. | Concordia University |
Keywords: Sensor networks, Optimization algorithms, Agents-based systems
Abstract: In this paper, an efficient deployment strategy is proposed for a network of mobile and static sensors with nonidentical sensing and communication radii. The multiplicatively weighted Voronoi (MW-Voronoi) diagram is used to partition the field and assign the underlying coverage task to each mobile sensor. A gradient-based method is applied to find the best candidate point based on the detected coverage holes and the coverage priority considering the relative distance of the mobile sensor from the static ones and the obstacles in the field. The sensors move to a new position if such a relocation increases their local coverage. The efficiency of the proposed strategy in different scenarios is demonstrated by simulations.
|
|
17:20-17:40, Paper FrC13.5 | |
>Classifier Design for Decentralised Sensing with Digital Communication |
|
Garg, Gauri | Indian Institute of Technology Bombay |
Khadilkar, Harshad | TATA Consultancy Services |
Kulkarni, Ankur A. | Indian Institute of Technology Bombay |
Paranjape, Aditya A | Tata Consultancy Services Ltd |
Keywords: Sensor fusion, Quantized systems, Decentralized control
Abstract: We consider the problem of classifying the operating mode of a plant, using distributed sensors and a digital channel. The abstract problem is formulated using simplifications, where the plant only has two modes, the sensors have independent and identically distributed (but possibly mode-dependent) measurement noise, and a noise-less digital communication channel. The objective is to design a combined distributed digitisation (quantisation) and centralised classification strategy that maximises accuracy while observing n messages, each of which can take k unique values. Even in this simplistic scenario, our analysis shows that (i) the optimal decision boundaries even in the fully observable (analog) case depend strongly on the assumptions about measurement noise, (ii) as a result, the classification strategy selection is non-trivial, and (iii) the distributed quantisation algorithm design also has a strong influence on the final classification accuracy. We support the analytical arguments by empirical simulation experiments.
|
|
17:40-18:00, Paper FrC13.6 | |
>Rigid Motion Gaussian Processes with SE(3) Kernel and Application to Visual Pursuit Control |
|
Omainska, Marco | The University of Tokyo |
Yamauchi, Junya | The University of Tokyo |
Lederer, Armin | Technical University of Munich |
Hirche, Sandra | Technische Universität München |
Fujita, Masayuki | The University of Tokyo |
Keywords: Uncertain systems, Machine learning, Stability of nonlinear systems
Abstract: We address the learning of unknown rigid body motions in the Special Euclidian Group SE(3) based on Gaussian Processes. A new covariance kernel for SE(3) is presented and proven to be a valid kernel for Gaussian Process Regression. The learning error of the proposed Gaussian Process model is extended to a high-probability statement on SE(3). We employ it in a visual pursuit scenario of a moving target with unknown velocity in 3D space. Our approach is validated in a simulated 3D environment in Unity, and shows significant better prediction accuracy than the most commonly used Gaussian kernel. When compared to other covariance kernels proposed on SE(3), its advantages are a natural extension of covering numbers on SE(3), that it is computationally more efficient, and that stability of target pursuit can be guaranteed without limiting the target rotational space to SO(2).
|
|
FrC14 |
Roselle Junior 4612 |
Observers for Nonlinear Systems II |
Regular Session |
Chair: Chopra, Nikhil | University of Maryland, College Park |
Co-Chair: Boyacioglu, Burak | University of Nevada, Reno |
|
16:00-16:20, Paper FrC14.1 | |
>Indirect Data-Driven Observer Design Using Neural Canonical Observer Structures |
|
Ecker, Lukas | Johannes Kepler University Linz, Institute of Automatic Control |
Schöberl, Markus | Johannes Kepler University Linz |
Keywords: Observers for nonlinear systems, Nonlinear systems identification, Neural networks
Abstract: An indirect data-driven observer design approach for nonlinear discrete-time systems based on an input-output injection with neural canonical observer structures is proposed. An artificial neural network auto-encoder structure, trained with recorded state, input, and output data, is used for the identification of a system in a nonlinear Brunovsky observer form with output transformation. The neural approximations of the transformations and the input-output injection can be used to construct an observer with linear error dynamics using methods from linear control theory. The approach is demonstrated on two academic examples and on an industrially-motivated problem with a sampled continuous-time model.
|
|
16:20-16:40, Paper FrC14.2 | |
>Empirical Individual State Observability |
|
Cellini, Benjamin | University of Nevada, Reno |
Boyacioglu, Burak | University of Nevada, Reno |
van Breugel, Floris | University of Nevada, Reno |
Keywords: Observers for nonlinear systems, Numerical algorithms, Sensor fusion
Abstract: A dynamical system is observable if there is a one-to-one mapping from the system's measured outputs and inputs to all of the system's states. Analytical and empirical tools exist for quantifying the (full state) observability of linear and nonlinear systems; however, empirical tools for evaluating the observability of individual state variables are lacking. Here, a new empirical approach termed Empirical Individual State Observability (E-ISO) is developed to quantify the level of observability of individual state variables. E-ISO first builds an empirical observability matrix via simulation, then determines the subset of its rows required to estimate each state variable individually. We present a convex optimization approach to do this efficiently. Finally, (un)observability measures for these subsets are calculated to provide independent estimates of the observability of each state variable. Multiple example applications of E-ISO on linear and nonlinear systems are shown to be consistent with analytical results. Broadly, E-ISO will be an invaluable tool both for designing active sensing control laws or optimizing sensor placement to increase the observability of individual state variables for engineered systems, and analyzing the trajectory decisions made by organisms.
|
|
16:40-17:00, Paper FrC14.3 | |
>Iteratively Preconditioned Gradient-Descent Approach for Moving Horizon Estimation Problems |
|
Liu, Tianchen | University of Maryland, College Park |
Chakrabarti, Kushal | Tata Consultancy Services Research |
Chopra, Nikhil | University of Maryland, College Park |
Keywords: Observers for nonlinear systems, Optimization
Abstract: Moving horizon estimation (MHE) is a state estimation method that has been extensively studied. The state estimates for the MHE problem are obtained by solving an approximation nonlinear optimization problem. This optimization process is known to be computationally challenging. This paper explores the idea of iteratively preconditioned gradient-descent (IPG) to solve the MHE issue to outperform the current solution methods in light of this limitation. To our knowledge, the preconditioning technique is employed for the first time in this research to speed up the critical MHE optimization stage and lower the computing cost. For a class of MHE problems, the proposed iterative approach’s convergence guarantee is shown. Sufficient conditions for the MHE problem to be convex are also derived. Finally, the proposed method is implemented on a unicycle localization example. The simulation results demonstrate that the proposed approach can improve accuracy with reduced computational costs.
|
|
17:00-17:20, Paper FrC14.4 | |
>Equivariant Filter for Feature-Based Homography Estimation for General Camera Motion |
|
Bouazza, Tarek | Laboratoire I3S UCA-CNRS |
Ashton, Katrina | University of Pennsylvania |
van Goor, Pieter | Australian National University |
Mahony, Robert | Australian National University, |
Hamel, Tarek | I3S-CNRS-UCA |
Keywords: Observers for nonlinear systems, Sensor fusion, Robotics
Abstract: Recent advances in nonlinear observer design for homography estimation have exploited the Lie group structure of SL(3). Existing work requires the group (homography) velocity input, while the available measurements are typically only the camera velocity. Consequently, prior contributions exploiting the SL(3) geometry either reconstruct the group velocity or restrict the camera motion to allow adaptive estimation of the group velocity online. This paper presents a novel symmetry-based approach to observer design for the more general problem of estimating both the homography and the structure parameters of a planar scene, allowing homography estimation for arbitrary trajectories using only camera velocity measurements and direct point-feature correspondences between images. A new Lie group is introduced for the homography and structure parameters, whose symmetry structure is exploited to establish the system and output equivariance properties. We show that the system kinematics admit an equivariant lift, and the proposed observer is then designed based on the recently developed Equivariant Filter framework. Simulation results demonstrate the performance and consistency of the proposed approach.
|
|
17:20-17:40, Paper FrC14.5 | |
>About a Possible High Poles Observer Design Instead of High Gain for Triangular Nonlinear Systems |
|
Besancon, Gildas | GIPSA-Lab, Grenoble INP, CNRS |
Keywords: Observers for nonlinear systems
Abstract: This paper is about observer design for a class of nonlinear systems admitting a possible solution via the well-known high-gain technique. Here instead, a design based on full pole placement for the linear part of the observer is discussed. In particular it is shown that exponential convergence of the observation error is guaranteed in spite of nonlinearities, for poles chosen large enough, with observer gains which can be lower than in a standard high gain approach. A focus is given on systems up to order three, and a discussion on measurement noise effect is provided. Simulation examples are included to illustrate the conclusions.
|
|
17:40-18:00, Paper FrC14.6 | |
>Robust Control Barrier Functions for Safe Control under Uncertainty Using Extended State Observer and Output Measurement |
|
Chen, Jinfeng | Cleveland State University |
Gao, Zhiqiang | Cleveland State Univ |
Lin, Qin | Cleveland State University |
Keywords: Uncertain systems, Observers for nonlinear systems, Optimal control
Abstract: Control barrier functions-based quadratic programming (CBF-QP) is gaining popularity as an effective controller synthesis tool for safe control. However, the provable safety is established on an accurate dynamic model and access to all states. To address such a limitation, this paper proposes a novel design combining an extended state observer (ESO) with a CBF for safe control of a system with model uncertainty and external disturbances only using output measurement. Our approach provides a less conservative estimation error bound than other disturbance observer-based CBFs. Moreover, only output measurements are needed to estimate the disturbances instead of access to the full state. The bounds of state estimation error and disturbance estimation error are obtained in a unified manner and then used for robust safe control under uncertainty. We validate our approach’s efficacy in simulations of an adaptive cruise control system and a Segway self-balancing scooter.
|
|
FrC15 |
Roselle Junior 4611 |
Uncertain Systems |
Regular Session |
Chair: Paschalidis, Ioannis Ch. | Boston University |
Co-Chair: Hsieh, Chung-Han | National Tsing Hua University |
|
16:00-16:20, Paper FrC15.1 | |
>Counter-Example Guided Inductive Synthesis of Control Lyapunov Functions for Uncertain Systems |
|
Masti, Daniele | IMT School for Advanced Studies Lucca |
Fabiani, Filippo | IMT School for Advanced Studies Lucca |
Gnecco, Giorgio | IMT - School for Advanced Studies |
Bemporad, Alberto | IMT School for Advanced Studies Lucca |
Keywords: Uncertain systems, Computer-aided control design, Lyapunov methods
Abstract: We propose a counter-example guided inductive synthesis (CEGIS) scheme for the design of control Lyapunov functions and associated state-feedback controllers for linear systems affected by parametric uncertainty with arbitrary shape. In the CEGIS framework, a learner iteratively proposes a candidate control Lyapunov function and a tailored controller by solving a linear matrix inequality (LMI) feasibility problem, while a verifier either falsifies the current candidate by producing a counter-example to be considered at the next iteration, or it certifies that the tentative control Lyapunov function actually enjoys such feature. We investigate the Lipschitz continuity of the objective function of the global optimization problem solved by the verifier, which is key to establish the convergence of our method in a finite number of iterations. Numerical simulations confirm the effectiveness of the proposed approach.
|
|
16:20-16:40, Paper FrC15.2 | |
>Design of Q-Filter-Based Disturbance Observer for Differential Algebraic Equations and a Robust Stability Condition: Zero Relative Degree Case |
|
Chang, Hamin | Seoul National University |
Trenn, Stephan | University of Groningen |
Keywords: Differential-algebraic systems, Robust control, Uncertain systems
Abstract: While the disturbance observer (DOB)-based controller is widely utilized in various practical applications, there has been a lack of extension of its use to differential algebraic equations (DAEs). In this paper, we introduce several lemmas that establish necessary and/or sufficient conditions for specifying the relative degree of DAEs. Using these lemmas, we also figure out that there is a class of DAEs which can be viewed as linear systems with zero relative degree. For the class of DAEs, we propose a design of Q-filter-based DOB as well as a robust stability condition for systems controlled by the DOB through time domain analysis using singular perturbation theory. The proposed stability condition is verified by an illustrative example.
|
|
16:40-17:00, Paper FrC15.3 | |
>A Stackelberg Game Approach to Control the Overall Load Consumption of a Residential Neighborhood |
|
Ozcan, Erhan Can | Boston University |
Paschalidis, Ioannis Ch. | Boston University |
Keywords: Optimization, Smart grid, Game theory
Abstract: This paper formulates a Stackelberg game between a coordination agent and participating homes to control the overall load consumption of a residential neighborhood. Each home optimizes a comfort-cost trade off to determine a load schedule of its available appliances in response to a price vector set by the coordination agent. The goal of the coordination agent is to find a price vector that will keep the overall load consumption of the neighborhood around some target value. After transforming the bilevel optimization problem into a single level optimization problem by using Karush-Kuhn-Tucker (KKT) conditions, we model how each home reacts to any change in the price vector by using the implicit function theorem. By using this information, we develop a distributed optimization framework based on gradient descent to attain a better price vector. We verify the load shaping capacity and the computational performance of the proposed optimization framework in a simulated environment establishing significant benefits over solving the centralized problem using commercial solvers.
|
|
17:00-17:20, Paper FrC15.4 | |
>Learning Adaptive Horizon Maps Based on Error Forecast for Model Predictive Control |
|
Gonzalez, Carlos | The University of Texas at Austin |
Bang, Seung Hyeon | The University of Texas at Austin |
Li, Po-han | The University of Texas at Austin |
Chinchali, Sandeep | UT Austin |
Sentis, Luis | The University of Texas at Austin |
Keywords: Predictive control for linear systems, Robotics, Optimization
Abstract: We present a model predictive control framework that uses varying prediction horizons according to the current forecasted uncertainties and estimated distance of the terminal state from its desired state. Our results suggest that the space of such optimal horizons, which we call horizon maps, is well structured for linear systems, meaning that it can be easily learned using tools from machine learning. Our approach is well suited for real-time control and can scale to higher dimensional systems. We also perform an analysis on the required quality of the datasets used to learn the horizon maps and conclude with results of this framework using an externally-driven, constrained linear quadratic regulator problem.
|
|
17:20-17:40, Paper FrC15.5 | |
>Learning Controllers from Data Via Kernel-Based Interpolation |
|
Hu, Zhongjie | University of Groningen |
De Persis, Claudio | University of Groningen |
Tesi, Pietro | University of Florence |
Keywords: Data driven control
Abstract: We propose a data-driven control design method for nonlinear systems that builds on kernel-based interpolation. Under some assumptions on the system dynamics, kernel-based functions are built from data and a model of the system, along with deterministic model error bounds, is determined. Then, we derive a controller design method that aims at stabilizing the closed-loop system by cancelling out the system nonlinearities. The proposed method can be implemented using semidefinite programming and returns positively invariant sets for the closed-loop system.
|
|
17:40-18:00, Paper FrC15.6 | |
>On Robustness of Double Linear Policy with Time-Varying Weights |
|
Wang, Xin-Yu | National Tsing Hua University |
Hsieh, Chung-Han | National Tsing Hua University |
Keywords: Finance, Stochastic systems, Time-varying systems
Abstract: In this paper, we extend the existing double linear policy by incorporating time-varying weights instead of constant weights and study a certain robustness property, called robust positive expectation (RPE), in a discrete-time setting. We prove that the RPE property holds by employing a novel elementary symmetric polynomials characterization approach and derive an explicit expression for both the expected cumulative gain-loss function and its variance. To validate our theory, we perform extensive Monte Carlo simulations using various weighting functions. Furthermore, we demonstrate how this policy can be effectively incorporated with standard technical analysis techniques, using the moving average as a trading signal.
|
|
FrC16 |
Peony Junior 4512 |
Control Applications |
Regular Session |
Chair: Julius, Agung | Rensselaer Polytechnic Institute |
Co-Chair: Barbot, Jean Pierre | ENSEA |
|
16:00-16:20, Paper FrC16.1 | |
>Direct Data-Driven Vibration Control for Adaptive Optics |
|
Gupta, Vaibhav | École Polytechnique Fédérale De Lausanne (EPFL) |
Karimi, Alireza | EPFL |
Wildi, François | Université De Genève |
Véran, Jean-Pierre | Herzberg Institute of Astrophysics |
Keywords: Control applications, Data driven control, Optimal control
Abstract: Adaptive optics (AO) systems are used in ground-based telescopes to improve image resolutions, especially for long-exposure photography, by compensating for the effects of atmospheric turbulence and internal vibrations. Most current AO systems are based on simple control laws that either neglect the temporal correlation in atmospheric turbulence, use a simplified system model, or both. This paper presents a direct data-driven control scheme to compute an optimal controller using the frequency-domain representation of the disturbance and the system model. Numerical simulations of the AO system demonstrate performance improvement compared to standard AO control schemes, and resilience to the variance in atmospheric turbulence and internal vibrations.
|
|
16:20-16:40, Paper FrC16.2 | |
>Flatness-Based Control Strategy for N Parallel Connected Boost Choppers and N Sources with Differing Characteristics |
|
Messaoudi, Souhir | Ecole Centrale Nantes, LS2N |
Nicolau, Florentina | Ensea Cergy |
Ghanes, Malek | Centrale Nantes |
Sbita, Lassaad | Ecole Nationale d’Ingenieurs De Gabes (ENIG) |
Barbot, Jean Pierre | Ecole Centrale Nantes & CNRS |
Keywords: Control applications, Feedback linearization, Power systems
Abstract: This paper presents a new control strategy based on a differential flatness approach for n boost choppers and n sources connected in parallel with different characteristics, the objective being to make them work on the same voltage bus. We first give an in-depth study of flatness of the n-boost system and propose a flat output for this type of boost choppers configuration, which ensures homogeneous power sharing among the choppers and guarantees continuous current in at least n − 1 choppers. Another contribution is the establishment of a relation between the proposed flat output and the regulation of the DC bus voltage via an additional power load control loop. To demonstrate the effectiveness of the proposed control strategy, the paper includes simulation results for three boost choppers and sources connected in parallel with different characteristics.
|
|
16:40-17:00, Paper FrC16.3 | |
>An LMI-Based Risk Assessment of Leader-Follower Multi-Agent System under Stealthy Cyberattacks |
|
Hwang, Sounghwan | Purdue University |
Cho, Minhyun | Purdue University |
Kim, Sungsoo | Purdue University |
Hwang, Inseok | Purdue University |
Keywords: Control applications, LMIs, Lyapunov methods
Abstract: This paper investigates a method for quantifying the potential risk from cyberattacks in multi-agent systems (MASs). Since MASs inherently rely on the communication between agents, the security vulnerabilities of the communication links make MASs more vulnerable to cyberattacks than single-agent systems. The impact of cyberattacks could lead to the disruption of performance or the violation of safety. To handle these limitations, we propose a risk assessment method for MASs using reachability analysis which computes the reachable set of the MASs via a Lyapunov function and its corresponding linear matrix inequalities (LMIs). The proposed method can quantify the potential risk against cyberattacks at agent and entire system levels by deriving ellipsoidal over-approximated reachable sets. An illustrative example is provided to validate the potency of the method, which shows the risk associated with the formation control of a leader-following MAS in an environment with scattered obstacles. The proposed method can help improve the safety of the MAS in various applications.
|
|
17:00-17:20, Paper FrC16.4 | |
>An Optimal Control Approach for Additive Manufacturing Production with Waste Recycling Process |
|
Wang, Shuo | University of Texas at Arlington |
Sarrafan, Arian | University of Texas at Arlington |
Di, Lei | University of Texas at Arlington |
Yang, Yiran | University of Texas at Arlington |
Keywords: Control applications, Manufacturing systems and automation
Abstract: Economic damage due to the supply chain turmoil in the past few years has been more severe than the pandemic, labor shortages, and domestic conflict combined. The primary cause of such a crisis is that the current supply chain analysis tool, relying heavily on static optimization, is insensitive to non-eligible changes such as policy changes due to the pandemic. As a result, such analysis needs to be conducted regularly whenever there is a change in the economic environment, which dramatically increases the computational cost. In this paper, the main purpose is to achieve agile sustainability supply chain management through dynamic system modeling and control for production processes of supply chain networks (SCNs), which involves both theoretical and numerical analysis. In particular, we first formulated a chain-like dynamic system to represent the daily production process, which is a discrete-time dynamic system from the control engineering perspective. Then, an optimal control problem can be developed for decision-making on production. Several numerical cases are presented in this paper to demonstrate the applicability of this developed dynamic system and further discuss the potential optimal production.
|
|
17:20-17:40, Paper FrC16.5 | |
>Optimal Control of Discrete-Time Multivariate Point Processes with Finite-Time Steady State |
|
Julius, Agung | Rensselaer Polytechnic Institute |
Wen, Yunshi | Rensselaer Polytechnic Institute |
Yan, Ruixuan | Rensselaer Polytechnic Institute |
Keywords: Control applications, Optimal control, Discrete event systems
Abstract: Multivariate point processes (MPP) are widely used to model the occurrence of multiple interrelated events in complex systems. They are used in a variety of fields to analyze data and define models that can make predictions about future events. In this paper, we consider finite-state MPP, which are products of finite state automata (FSA) and MPP. Specifically, the events in the MPP trigger state transitions in the FSA, while the intensities of the point processes are defined as functions of the FSA state and the history of the MPP. Further, we assume that some of the event types are controllable, i.e., they are not random but can be triggered. We formulate an optimal control problem for such system, which can then be expressed as optimal control for a Markov Decision Process (MDP) with infinite states. When the system has appropriate finite-time steady state properties, we use the concept of stochastic bisimulation of MDP to reduce the MDP into a finite state one, thereby allowing us to use standard optimal control techniques to calculate the optimal policy. We demonstrate the effectiveness of our method on a simplified sleep-wake cycle model, for the problem of optimally scheduling naps to maximize the length of wakefulness intervals.
|
|
17:40-18:00, Paper FrC16.6 | |
>Coordinated Control of Load Tap Changer Transformers for Voltage Regulation and Voltage Hunting Prevention: A Switched Systems Approach |
|
Jaramillo, Ismael | Brandenburg University of Technology Cottbus-Senftenberg |
Mercado Uribe, José Angel | Brandenburgische Technische Universität Cottbus-Senftenberg |
Schiffer, Johannes | Brandenburg University of Technology |
Keywords: Control applications, Power systems, Switched systems
Abstract: We propose a coordinated control strategy for load tap changer (LTC) transformers in high voltage radial transmission systems that are connected to higher voltage grids and active distribution networks. We utilize switched systems modeling tools to capture the non-smooth characteristics of the LTCs. Our approach employs a state- and time-dependent switching logic to regulate the voltage at a specific node while preventing stability issues produced by the voltage hunting phenomenon. Then, we derive sufficient tuning conditions for the LTC control parameters, namely, deadband widths and time delays, as a function of the tap magnitude of the LTCs. These conditions ensure the existence of an exponentially stable equilibrium point of the closed-loop switched system and the exponential convergence of its output, i.e., the regulated voltage, to a desired set. Finally, a numerical example shows the proposed strategy’s superior performance over an uncoordinated scenario.
|
|
FrC17 |
Peony Junior 4511 |
Intelligent Systems |
Regular Session |
Chair: Bai, Ting | KTH Royal Institute of Technology |
Co-Chair: Seel, Thomas | Leibniz Universität Erlangen |
|
16:00-16:20, Paper FrC17.1 | |
>Turing Meets Machine Learning: Uncomputability of Zero-Error Classifiers |
|
Boche, Holger | Technische Universitaet Muenchen |
Böck, Yannik | Technical University of Munich |
Speidel, Stefanie | National Center for Tumor Diseases (NCT) |
Fitzek, Frank | Technical University of Dresden |
Keywords: Pattern recognition and classification, Intelligent systems, Computational methods
Abstract: In almost all areas of information technology, the importance of automated decision-making based on intelligent algorithms has been increasing steadily within recent years. Since many of the envisioned near-future applications of these algorithms involve critical infrastructure or sensitive human goods, a sound theoretical basis for integrity assessment is required, if for no other reason than the legal accountability of system operators. This article aims to contribute to the understanding of integrity of automated decision-making under the aspect of fundamental mathematical models for computing hardware. To this end, we apply the theory of Turing machines to the problem of separating the support sets of smooth functions, which provides a simple yet mathematically rigorous framework for support-vector machines on digital computers. Further, we investigate characteristic quantities and objects, such as the distance between two separated support sets, or separating hyperplanes themselves, with regards to their computability properties, and provide non-technical interpretations of our findings in the context of machine learning and technological trustworthiness.
|
|
16:20-16:40, Paper FrC17.2 | |
>Visual Concept Formation Using a Dynamic System |
|
Gong, Weibo | Univ. of Massachusetts at Amherst |
Zylstra, Bradley | University of Massachusetts Amherst |
Keywords: Intelligent systems, Learning, Biologically-inspired methods
Abstract: Spatial signal processing algorithms often use pregiven coordinate systems to label pixel positions. These processing algorithms are thus burdened by an external reference grid, making the acquisition of relative, intrinsic features difficult. This is in contrast to animal vision and cognition: animals recognize features without an external coordinate system. We show that a visual signal processing algorithm with content based addressing is not only important for animal vision, but also fundamental for concept formation. In this paper we start with a visual object deformation transfer experiment. We then formulate an algorithm that achieves deformation invariance with relative coordinates. The paper concludes with the implications for general concept formation.
|
|
16:40-17:00, Paper FrC17.3 | |
>Neural ODEs for Data-Driven Automatic Self-Design of Finite-Time Output Feedback Control for Unknown Nonlinear Dynamics |
|
Bachhuber, Simon | FAU Erlangen-Nürnberg |
Weygers, Ive | FAU Erlangen-Nürnberg |
Seel, Thomas | Leibniz Universität Erlangen |
Keywords: Intelligent systems, Machine learning, Neural networks
Abstract: Many application fields, e.g., robotic surgery, autonomous piloting, and wearable robotics greatly benefit from advances in robotics and automation. A common task is to control an unknown nonlinear system such that its output tracks a desired reference signal for a finite duration of time. A learning control method that automatically and efficiently designs output feedback controllers for this task would greatly boost practicality over time-consuming and labour-intensive manual system identification and controller design methods. In this contribution we propose Automatic Neural Ordinary Differential Equation Control (AN- ODEC), a data-efficient automatic design of output feedback controllers for finite-time reference tracking in systems with unknown nonlinear dynamics. In a two-step approach, ANODEC first identifies a neural ODE model of the system dynamics from input-output data of the system dynamics and then exploits this data-driven model to learn a neural ODE feedback controller, while requiring no knowledge of the actual system state or its dimensionality. In-silico validation shows that ANODEC is able to —automatically— design competitive controllers that outperform two controller baselines, and achieves an on average ≈ 30% / 17% lower median RMSE. This is demonstrated in four different nonlinear systems using multiple, qualitatively different and even out-of-training-distribution reference signals.
|
|
17:00-17:20, Paper FrC17.4 | |
>Cut Sequencing Algorithm for Safely Disassembling Large Structures |
|
Akl, James | Worcester Polytechnic Institute |
Pericherla, Sumanth | Worcester Polytechnic Institute |
Calli, Berk | Worcester Polytechnic Institute |
Keywords: Intelligent systems, Modeling, Simulation
Abstract: Disassembly and fragmentation are key operations in the dismantling and recycling of decommissioned structures such as aircraft, vessels, and buildings. Often, such operations are hazardous requiring careful planning for safe execution based on the experience and intuition of workers and forepersons. We propose and devise an algorithm for the automated sequencing of cuts to disassemble large structures. Using feedback from physics-based simulations and a mathematical model for safety, our algorithm performs sequential decision-making yielding the order of the cuts on the structure and the corresponding safe standing positions of the cutter (representing a worker or a robot). Our goal is to determine a sequence of cuts and cutter locations to maximize safety for the cutter and the environment. We establish the optimal solution via exhaustive searching, and design a greedy decision scheme to reduce the search runtime. Using our evaluations in simulation, we compare our greedy decision scheme against exhaustive searching and random searching, concluding that it satisfices the goal with high safety scores and low runtime.
|
|
17:20-17:40, Paper FrC17.5 | |
>Necessary and Sufficient Conditions for Satisfying Linear Temporal Logic Constraints Using Control Barrier Certificates (I) |
|
Niu, Luyao | University of Washington |
Clark, Andrew | Washington University in St. Louis |
Poovendran, Radha | University of Washington |
Keywords: Autonomous systems, Intelligent systems
Abstract: Temporal logic specifications have been used to express complex tasks for control systems. Discretization-free approaches, which do not require discretizing the state and input spaces of the system, have been proposed for control synthesis under temporal logic specifications. Among these approaches, control barrier certificate (CBC)-based solutions have attracted increasing attention. The existing CBC-based approaches, however, have no guarantee on always finding control laws to satisfy the specification, and hence are sound but not complete. In this paper, we derive the necessary and sufficient conditions for a control law to satisfy a temporal logic specification over finite traces using CBCs. By leveraging the equivalence between satisfying the specification and violating the negated specification, we first negate the specification and construct the deterministic finite automaton (DFA) as a representation. We then decompose the DFA into a set of safety problems, where each decomposed problem corresponds to a transition in the DFA. We derive the necessary and sufficient conditions for a control law to solve each safety problem via CBC-based approach. We further develop the necessary and sufficient conditions to verify whether the control laws associated with different safety problems are composable or not. The composability captures whether a sequence of transitions in the DFA can be realized by the system or not. If the set of composable control laws does not render an accepting run on the DFA, then the system can satisfy the specification. We illustrate the proposed approach using a numerical case study on a multi-agent system.
|
|
17:40-18:00, Paper FrC17.6 | |
>Rollout-Based Charging Strategy for Electric Trucks with Hours-Of-Service Regulations |
|
Bai, Ting | KTH Royal Institute of Technology |
Li, Yuchao | KTH Royal Institute of Technology |
Johansson, Karl H. | KTH Royal Institute of Technology |
Mårtensson, Jonas | KTH Royal Institute of Technology |
Keywords: Autonomous vehicles, Optimal control, Transportation networks
Abstract: Freight drivers of electric trucks need to design charging strategies for where and how long to recharge the truck in order to complete delivery missions on time. Moreover, the charging strategies should be aligned with drivers' driving and rest time regulations, known as hours-of-service (HoS) regulations. This letter studies the optimal charging problems of electric trucks with delivery deadlines under HoS constraints. We assume that a collection of charging and rest stations is given along a pre-planned route with known detours and that the problem data are deterministic. The goal is to minimize the total cost associated with the charging and rest decisions during the entire trip. This problem is formulated as a mixed integer program with bilinear constraints, resulting in a high computational load when applying exact solution approaches. To obtain real-time solutions, we develop a rollout-based approximate scheme, which scales linearly with the number of stations while offering solid performance guarantees. We perform simulation studies over the Swedish road network based on realistic truck data. The results show that our rollout-based approach provides near-optimal solutions to the problem in various conditions while cutting the computational time drastically.
|
|
FrC18 |
Peony Junior 4412 |
Lyapunov Methods |
Regular Session |
Chair: Mo, Yuanqiu | Southeast University |
Co-Chair: Hou, Huazhou | RMIT University |
|
16:00-16:20, Paper FrC18.1 | |
>Auxiliary-Variable Adaptive Control Barrier Functions for Safety Critical Systems |
|
Liu, Shuo | Boston University |
Xiao, Wei | Massachusetts Institute of Technology |
Belta, Calin | Boston University |
Keywords: Lyapunov methods, Constrained control, Optimal control
Abstract: This paper studies safety guarantees for systems with time-varying control bounds. It has been shown that optimizing quadratic costs subject to state and control constraints can be reduced to a sequence of Quadratic Programs (QPs) using Control Barrier Functions (CBFs). One of the main challenges in this method is that the CBF-based QP could easily become infeasible under tight control bounds, especially when the control bounds are time-varying. The recently proposed adaptive CBFs have addressed such infeasibility issues, but require extensive and non-trivial hyperparameter tuning for the CBF-based QP and may introduce overshooting control near the boundaries of safe sets. To address these issues, we propose a new type of adaptive CBFs called Auxiliary-Variable Adaptive CBFs (AVCBFs). Specifically, we introduce an auxiliary variable that multiplies each CBF itself, and define dynamics for the auxiliary variable to adapt it in constructing the corresponding CBF constraint. In this way, we can improve the feasibility of the CBF-based QP while avoiding extensive parameter tuning with non-overshooting control since the formulation is identical to classical CBF methods. We demonstrate the advantages of using AVCBFs and compare them with existing techniques on an Adaptive Cruise Control (ACC) problem with time-varying control bounds.
|
|
16:20-16:40, Paper FrC18.2 | |
>Optimization-Based Constrained Funnel Synthesis for Systems with Lipschitz Nonlinearities Via Numerical Optimal Control |
|
Kim, Taewan | University of Washington |
Elango, Purnanand | University of Washington |
Reynolds, Taylor Patrick | University of Washington |
Acikmese, Behcet | University of Washington |
Mesbahi, Mehran | University of Washington |
Keywords: Lyapunov methods, LMIs, Robust control
Abstract: This paper presents a funnel synthesis algorithm for computing controlled invariant sets and feedback control gains around a given nominal trajectory for dynamical systems with locally Lipschitz nonlinearities and bounded disturbances. The resulting funnel synthesis problem involves a differential linear matrix inequality (DLMI) whose solution satisfies a Lyapunov condition that implies invariance and attractivity properties. Due to these properties, the proposed method can balance maximization of initial invariant funnel size, i.e., size of the funnel entry, and minimization of the size of the attractive funnel for disturbance attenuation. To solve the resulting funnel synthesis problem with the DLMI as one of the problem constraints, we employ a numerical optimal control approach that uses a multiple shooting method to convert the problem into a finite dimensional semidefinite programming problem. This framework avoids the need for piecewise linear system matrices and funnel parameters, which are typically assumed in recent related work. We illustrate the proposed funnel synthesis method with a numerical example.
|
|
16:40-17:00, Paper FrC18.3 | |
>Zero-Shot Transferable and Persistently Feasible Safe Control for High Dimensional Systems by Consistent Abstraction |
|
Wei, Tianhao | Carnegie Mellon University |
Kang, Shucheng | Harvard University |
Liu, Ruixuan | Carnegie Mellon University |
Liu, Changliu | Carnegie Mellon University |
Keywords: Lyapunov methods, Hierarchical control, Constrained control
Abstract: Safety is critical in robotic tasks. Energy function based methods have been introduced to address the problem. To ensure safety in the presence of control limits, we need to design an energy function that results in persistently feasible safe control at all system states. However, designing such an energy function for high-dimensional nonlinear systems remains challenging. Considering the fact that there are redundant dynamics in high dimensional systems with respect to the safety specifications, this paper proposes a novel approach called abstract safe control. We propose a system abstraction method that enables the design of energy functions on a low-dimensional model. Then we can synthesize the energy function with respect to the low-dimensional model to ensure persistent feasibility. The resulting safe controller can be directly transferred to other systems with the same abstraction, e.g., when a robot arm holds different tools. The proposed approach is demonstrated on a 7-DoF robot arm (14 states) both in simulation and real-world. Our method always finds feasible control and achieves zero safety violations in 500 trials on 5 different systems.
|
|
17:00-17:20, Paper FrC18.4 | |
>Formation Control of Differential-Drive Robots with Input Saturation and Constraint on Formation Size |
|
Agrawal, Ayush | Indian Institute of Technology Bombay |
Bharatheesha, Mukunda | ARTPARK, Indian Institute of Science |
Nadubettu Yadukumar, Shishir | Indian Institute of Science |
Keywords: Lyapunov methods, Nonlinear output feedback, Cooperative control
Abstract: Cooperative control involves developing control strategies for individual robots that guarantee synchronized behavior of the states of all the robots in a team in some prescribed sense. This work presents a novel controller that achieves formation control for a group of differential-drive robots. First, we propose a nonlinear feedback control law that guarantees stable tracking of a reference trajectory for a single robot without exceeding the velocity limits of the robot. Using Lyapunov analysis, we obtain the necessary conditions on the control parameters and establish ultimate boundedness on error terms. Next, we formulate the formation control problem as a trajectory tracking problem for the multi-robot system and solve it using the proposed controller. Additionally, we provide constraints on formation size for a planned reference trajectory, ensuring smooth cornering of multi-robot formation without exceeding actuation limits.
|
|
17:20-17:40, Paper FrC18.5 | |
>Safety of the Stanley Controller with Curved Lanes and Noisy Perception |
|
Li, Hongyi | University of Illinois Urbana-Champaign |
Mitra, Sayan | University of Illinois |
Keywords: Lyapunov methods, Nonlinear systems, Autonomous vehicles
Abstract: The Stanley controller was designed for the DARPA 2005 Grand Challenge and has been widely used in real autonomous vehicles and simulation models. While the original paper presented an analysis of the tracking performance of this controller with straight roads, the analysis for general curved lanes and with perception errors is not available. We utilize Lyapunov theory to give tracking performance guarantees for the Stanley controller. Our analysis can be used for assuring safety of lane following and provide guidelines for choosing design parameters with respect to velocity, lane curvation, and sensing constraints.
|
|
17:40-18:00, Paper FrC18.6 | |
>Finite Time Input-To-State Stability of Discrete Time Autonomous Systems |
|
Mo, Yuanqiu | Southeast University |
Xing, Ran | The University of Sydney |
Hou, Huazhou | Purple Mountain Laboratories |
Dasgupta, Soura | Univ. of Iowa |
Keywords: Lyapunov methods, Stability of nonlinear systems
Abstract: Finite time input-to-state stability, is an important extension of the classical input-to-state stability, where the state enters into a neighbourhood of the origin of a size determined by the input size in a finite time. In this paper, we address the finite time input-to-state stability of discrete time autonomous systems. We provide several types of Lyapunov functions that guarantee the finite time input-to-state stability of discrete time systems and characterize their equivalence. We also give a converse Lyapunov theorems correcting a mistake in [15].
|
|
FrC19 |
Peony Junior 4411 |
Kalman Filtering |
Regular Session |
Chair: Pascucci, Federica | University of Roma TRE |
Co-Chair: Bonnabel, Silvere | Mines ParisTech |
|
16:00-16:20, Paper FrC19.1 | |
>A Computationally Efficient Global Indicator to Detect Spurious Measurement Drifts in Kalman Filtering |
|
Parellier, Colin | Mines ParisTech |
Barrau, Axel | Safran |
Bonnabel, Silvere | Mines Paris PSL |
Keywords: Kalman filtering, Estimation, Identification
Abstract: We consider the problem of detecting additive structured correlated perturbations affecting the measurement outputs of a system whose state is estimated by a Kalman filter. We advocate the time series of the gradients of the log-likelihood with respect to the output measurements as an indicator, notably through its fast Fourier transform (FFT). This provides a novel unifying method to detect structured perturbations, namely small sinusoidal perturbations with unknown frequency, and slowly growing errors, such as a ramp, or more generally any known incipient profile with unknown starting time. The method allows for identification of their parameters too, i.e., frequency, and starting time of the ramp. Thanks to recent results on backpropagation in Kalman filters, and the use of the FFT, the method remains numerically tractable even for large datasets, as demonstrated by simulations.
|
|
16:20-16:40, Paper FrC19.2 | |
>Stability Analysis for Multirate Interlaced Kalman Filter |
|
Bonagura, Valeria | Roma Tre University |
Foglietta, Chiara | University of Roma TRE |
Panzieri, Stefano | Univ. "Roma Tre" |
Pascucci, Federica | University of Roma TRE |
Keywords: Kalman filtering, Estimation, Observers for nonlinear systems
Abstract: Distributed systems are often chosen since centralized solutions are often impractical when dealing with state estimation of complex systems due to computational complexity. The Interlaced Extended Kalman Filter is a distributed state observer that enables each subsystem to predict a subset of the state space and communicate with other subsystems. However, the Interlaced Extended Kalman Filter requires precise synchronization between subsystems, which may be unfeasible when, for instance, the sampling rates of the subsystems vary. To address this issue, this paper suggests an Interlaced Extended Kalman Filter extension that enables each subsystem to use the most recent estimate when up-to-date information is unavailable. Adjusting the covariance matrix, which can be done using Age of Information metrics, increases the uncertainty in the approximation. Each subsystem's stability is investigated, showing that changes in the covariance matrix do not affect the analysis. The suggested algorithm is validated in a scenario with four water tanks fed by two pumps, where the operating rates of the subsystems are different but fixed. The findings demonstrate that the proposed algorithm successfully handles the multi-rate problem while striking a reasonable balance between convergence rate and efficiency.
|
|
16:40-17:00, Paper FrC19.3 | |
>Optimized Data Selection for Nonlinear Filtering |
|
Soubaras, Jean-Baptiste | ENSTA Paris Tech |
Chahbazian, Clément | MBDA France |
Keywords: Kalman filtering, Estimation, Optimization algorithms
Abstract: Nonlinear estimation is ubiquitous in control and signal processing. It aims to estimate the most probable state of a system and its range of uncertainty by fusing data from multiple sensors over time using a filter. Although many efficient filters exist in the literature, their computational cost may increase when the set of data to process is significant. Besides, some data can be redundant or bring little information to the estimation of the state. In that case, their processing is costly and does not contribute to the filter's estimation. This paper introduces a semi-heuristic method to select a relevant subset of observations from a more extensive set of available data, using a cost function based on the approximation of the Cramer-Rao Lower Bound. This approach is adopted on an angles-only optimal navigation scenario where an extensive signal set is available. The results show that the filter achieves close-to-optimal accuracy for a lower computational cost.
|
|
17:00-17:20, Paper FrC19.4 | |
>Maximum Correntropy Ensemble Kalman Filter |
|
Tao, Yangtianze | Tsinghua University |
Kang, Jiayi | Tsinghua University |
Yau, Stephen S.-T. | Tsinghua University |
Keywords: Kalman filtering, Filtering, Stochastic systems
Abstract: In this article, a robust ensemble Kalman filter (EnKF) called MC-EnKF is proposed for nonlinear state-space model to deal with filtering problems with non-Gaussian observation noises. Our MC-EnKF is derived based on maximum correntropy criterion (MCC) with some technical approximations. Moreover, we propose an effective adaptive strategy for kernel bandwidth selection. Besides, the relations between the common EnKF and MC-EnKF are given, i.e., MC-EnKF will converge to the common EnKF when the kernel bandwidth tends to infinity. This justification provides a complementary understanding of the kernel bandwidth selection for MC-EnKF. In experiments, non-Gaussian observation noises significantly reduce the performance of the common EnKF for both linear and nonlinear systems, whereas our proposed MC-EnKF with a suitable kernel bandwidth maintains its good performance at only a marginal increase in computing cost, demonstrating its robustness and efficiency to non-Gaussian observation noises.
|
|
17:20-17:40, Paper FrC19.5 | |
>Invariant Kalman Filtering with Noise-Free Pseudo-Measurements |
|
Goffin, Sven | University of Liège |
Bonnabel, Silvere | Mines ParisTech |
Bruls, Olivier | University of Liege |
Sacré, Pierre | University of Liège |
Keywords: Kalman filtering, Nonlinear systems, Algebraic/geometric methods
Abstract: In this paper, we focus on developing an Invariant Extended Kalman Filter (IEKF) for extended pose estimation for a noisy system with state equality constraints. We treat those constraints as noise-free pseudo-measurements. To this aim, we provide a formula for the Kalman gain in the limit of noise-free measurements and rank-deficient covariance matrix. We relate the constraints to group-theoretic properties and study the behavior of the IEKF in the presence of such noise-free measurements. We illustrate this perspective on the estimation of the motion of the load of a overhead crane, when a wireless inertial measurement unit is mounted on the hook.
|
|
17:40-18:00, Paper FrC19.6 | |
>Rapid Transfer Alignment for Large and Time-Varying Attitude Misaligment Angles |
|
Tosoni, Laetitia | Thales |
Pham, Minh Tu | INSA De Lyon |
Massioni, Paolo | INSA Lyon |
Broussard, Elliot | Thales |
Keywords: Kalman filtering, Sensor fusion, Mechatronics
Abstract: Transfer alignment is an effective method to estimate the attitude difference between two inertial platforms. Traditional transfer alignment methods are either meant for small misalignments or use nonlinear filtering. Linear methods for large misalignments use quaternion attitude representation, but their performance degrades when the misalignment is not constant or slowly varying. This work proposes to apply rapid transfer alignment to the inertial stabilization of a Satcom On The Move antenna. In this application case, the two inertial platforms are connected by a kinematic chain, meaning the attitude difference between the inertial platforms is both large and time-varying. This work proposes a method to estimate this attitude difference. A Kalman filter is used for the estimation of the unknown angles. To that effect, a new propagation model is developed to take into account the misalignment variations using master and slave rotation rates. Simulation results show the performance of the proposed solution in a Satcom antenna inertial stabilization case.
|
|
FrC20 |
Orchid Junior 4312 |
Mechatronics |
Invited Session |
Chair: Boker, Almuatazbellah | Virginia Tech |
Co-Chair: Al Janaideh, Mohammad | University of Guelph |
Organizer: Flores, Gerardo | Center for Research in Optics |
Organizer: Al Janaideh, Mohammad | University of Guelph |
Organizer: Rakotondrabe, Micky | ENIT Tarbes, INPT, University of Toulouse |
Organizer: Heertjes, Marcel | Eindhoven University of Technology |
Organizer: Boker, Almuatazbellah | Virginia Tech |
|
16:00-16:20, Paper FrC20.1 | |
>Data-Driven Event-Triggered Bipartite Consensus for Multi-Agent Systems Preventing DoS Attacks |
|
Zhao, Huarong | JiangNan University |
Shan, Jinjun | York University |
Peng, Li | Jiangnan University |
Yu, Hongnian | Edinburgh Napier University |
Keywords: Agents-based systems, Cooperative control, Networked control systems
Abstract: This paper considers event-triggered bipartite consensus issues for discrete-time nonlinear networked multi-agent systems with antagonistic interactions and denial-of-service (DoS) attacks. Firstly, a pseudo partial derivative technology is applied to obtain an equivalent dynamic linearization model of the controlled system. A signed graph theory is employed to analyze the coopetition relationships among agents. Then, a distributed combined measurement error function is formulated to transform the bipartite consensus issue into a consensus issue. Meanwhile, an output predictive compensation scheme is proposed to offset the influence of DoS attacks. Furthermore, a dead-zone operator is designed to improve the flexibility of the proposed event-triggered mechanism. Subsequently, a data-driven event-triggered resilient bipartite consensus scheme is formulated. Then, the convergence of the proposed method is strictly proved by using the Lyapunov theory and the contraction mapping principle, which indicates that the bipartite consensus error will be cut to a small region around zero. Finally, hardware tasks are conducted to verify the effectiveness of the proposed method.
|
|
16:20-16:40, Paper FrC20.2 | |
>Classical Bouc-Wen Hysteresis Modeling and Force Control of a Piezoelectric Robotic Hand Manipulating a Deformable Object |
|
Flores, Gerardo | Center for Research in Optics |
Rakotondrabe, Micky | ENIT Tarbes, INPT, University of Toulouse |
Keywords: Mechatronics, Robotics, Nonlinear output feedback
Abstract: This letter focuses on the modeling and control of a piezoelectric actuator that is designed to manipulate objects. This research considers both the non-linearity caused by the hysteresis of the actuator and the deformation of the object being manipulated. To approximate the hysteresis, a classical Bouc-Wen model is used. To stabilize the force-tracking error, we propose a novel control approach combining three advanced methodologies: an output-feedback method based on a nonlinear observer, a Barrier-Lyapunov function design, and bounded control based on saturation functions. Combining these three powerful techniques produces a bounded and highly robust controller that can effectively reject aggressive disturbances while maintaining the tracking error inside a predefined set. Under such a scenario, it is demonstrated that the equilibrium point of the closed-loop system is asymptotically stable. The effectiveness of the proposed control method is validated through extensive numerical simulations.
|
|
16:40-17:00, Paper FrC20.3 | |
>Control Framework for a UAV Slung-Payload Transportation System |
|
Kang, Junjie | York University |
Shan, Jinjun | York University |
Alkomy, Hassan | York University |
Keywords: Autonomous vehicles, Hierarchical control, Stability of nonlinear systems
Abstract: This paper presents a control framework for transporting a UAV slung-payload, which can asymptotically stabilize not only the UAV but also the tether swing angles. By separating the system into two subsystems, the cascade control methodology is used to design the framework, which includes two sufficient conditions and suits for a large class of existing controllers. The control framework is strictly proved with the boundness of all states such that it can guarantee the asymptotic stability of the closed-loop overall system over the entire configuration space. Then, this framework is applied to a UAV trajectory tracking control problem with stability analysis. Samples of controllers are presented in the type of saturation or dynamic feedback. Finally, numerical and experimental validations are carried out on a UAV slung-payload transportation.
|
|
17:00-17:20, Paper FrC20.4 | |
>Fourth-Order Reference Trajectories in Lithography Stages with Weakly-Damped Modes - a Frequency-Domain Perspective (I) |
|
Heertjes, Marcel | Eindhoven University of Technology |
Zenteno Torres, Jazmin | Universite De Bordeaux |
Al Janaideh, Mohammad | University of Guelph |
Keywords: Mechatronics, Linear systems, Control applications
Abstract: The tracking accuracy in motion control systems like the moving stages in lithography machines, e.g., wafer scanners or metrology inspection tools, is partly determined by how the frequency content of its reference trajectories is transferred to the closed loop tracking error. In this regard, fourth-order reference trajectories for point-to-point motion will be studied from a frequency-domain perspective. By appropriately pairing the maximum snap and maximum jerk values, weakly-damped modes in the closed-loop response can be robustly dealt with without introducing a penalty on throughput.
|
|
17:20-17:40, Paper FrC20.5 | |
>Singular Perturbation-Based Approach for Robust Control of Reluctance-Actuated Motion Systems (I) |
|
Al Saaideh, Mohammad | Memorial University of Newfoundland |
Boker, Almuatazbellah | Virginia Tech |
Al Janaideh, Mohammad | University of Guelph |
Keywords: Mechatronics
Abstract: This paper introduces a new composite control approach for a motion system driven by a reluctance actuator. To achieve high-performance control, the method leverages singular perturbation theory to divide the problem into two components: a fast control problem and a slow control problem. A feedforward controller is developed based on the reduced system to address the fast control problem. The dynamic model is then formulated using the feedforward control law to address the slow control problem. Full-state feedback control chooses the input signal that results in the desired reference signal. The output signal of the feedback control is treated as the desired input for the feedforward controller. With the proposed approach, the feedforward controller for the fast dynamic eliminates the need for measuring the fast states. The effectiveness of the proposed approach is demonstrated through experimental testing.
|
|
17:40-18:00, Paper FrC20.6 | |
>Data-Driven Bayesian Control of Port-Hamiltonian Systems (I) |
|
Beckers, Thomas | Vanderbilt University |
Keywords: Mechatronics, Machine learning, Uncertain systems
Abstract: Port-Hamiltonian theory is an established way to describe nonlinear physical systems widely used in various fields such as robotics, energy management, and mechanical engineering. This has led to considerable research interest in the control of Port-Hamiltonian systems, resulting in numerous model-based control techniques. However, the performance and stability of the closed-loop typically depend on the quality of the PH model, which is often difficult to obtain using first principles. We propose a Gaussian Processes (GP) based control approach for Port-Hamiltonian systems (GPC-PHS) by leveraging gathered data. The Bayesian characteristics of GPs enable the creation of a distribution encompassing all potential Hamiltonians instead of providing a singular point estimate. Using this uncertainty quantification, the proposed approach takes advantage of passivity-based robust control with interconnection and damping assignment to establish probabilistic stability guarantees.
|
|
FrC21 |
Orchid Junior 4311 |
Aerospace Systems |
Regular Session |
Chair: Cenedese, Angelo | University of Padova |
Co-Chair: Manchester, Zachary | Carnegie Mellon University |
|
16:00-16:20, Paper FrC21.1 | |
>Quaternion-Based Non-Singular Terminal Sliding Mode Control for a Satellite-Mounted Space Manipulator |
|
Giordano, Jacopo | University of Padova |
Cenedese, Angelo | University of Padova |
Keywords: Aerospace, Control applications, Robust control
Abstract: In this paper, a robust control solution for a satellite equipped with a robotic manipulator is presented. First, the dynamic model of the system is derived based on quaternions to describe the evolution of the attitude of the base satellite. Then, a non-singular terminal sliding mode controller that employs quaternions for attitude control, is proposed for concurrently handling all the degrees of freedom of the space manipulator. Moreover, an additional adaptive term is embedded in the controller to estimate the upper bounds of disturbances and uncertainties. The result is a resilient solution able to withstand unmodelled dynamics and interactions. Lyapunov theory is used to prove the stability of the controller and numerical simulations allow assessing performance and fuel efficiency.
|
|
16:20-16:40, Paper FrC21.2 | |
>Safe Control Synthesis for Multicopter Via Control Barrier Function Backstepping |
|
Kim, Jinrae | Seoul National University |
Kim, Youdan | Seoul National University |
Keywords: Aerospace, Flight control, Constrained control
Abstract: A safe controller for multicopter is proposed using control barrier function. Multicopter dynamics is reformulated to deal with mixed-relative-degree and non-strict-feedback-form dynamics, and a time-varying safe backstepping controller is designed. Despite the time-varying variation, it is proven that the control input can be obtained by solving quadratic programming with affine inequality constraints. The proposed controller does not utilize a cascade control system design, unlike existing studies on the safe control of multicopter. Various safety constraints on angular velocity, total thrust direction, velocity, and position can be considered. Numerical simulation results support that the proposed safe controller does not violate all safety constraints including low- and high-level dynamics.
|
|
16:40-17:00, Paper FrC21.3 | |
>Cooperative Nonlinear Aircraft Defense Using Super Twisting Algorithm with State Constraints |
|
Gurjar, Bhagyashri | Indian Institute of Technology, Bombay |
Kumar, Shashi Ranjan | Indian Institute of Technology Bombay |
Mukherjee, Dwaipayan | Indian Institute of Technology Bombay |
Keywords: Aerospace, Lyapunov methods, Variable-structure/sliding-mode control
Abstract: This paper addresses the problem of cooperative guidance design for aircraft defense systems involving a target, a defender, and an attacker, using a super-twisting algorithm and barrier Lyapunov function. The system dynamics involve unknown functions, which are treated like disturbances and estimated using an observer. Imposing practical assumptions on the lateral accelerations of the vehicles, we propose a robust guidance design also to constrain the system states by definite bounds. We derived the controller using generalized triangle guidance concepts that provide these bounds for the states. Guidance commands are derived without any kind of linearizations that enable a wider domain of applicability of the proposed approach. The convergence is analyzed using a Lyapunov function. Simulation results are presented to study the efficacy of the proposed approach.
|
|
17:00-17:20, Paper FrC21.4 | |
>Time-Fuel-Optimal Navigation of a Commercial Aircraft in Cruise with Heading and Throttle Controls Using Pontryagin's Maximum Principle |
|
Jafarimoghaddam, Amin | Carlos 3 De Madrid Universidad |
Soler, Manuel | Universidad Carlos III De Madrid |
Keywords: Aerospace, Optimal control, Closed-loop identification
Abstract: In this letter, we consider the commercial aircraft trajectory optimization problem for a general cruise model with arbitrary spatial wind fields to be solved using the Pontryagin's maximum principle. The model features two fundamental controls, namely "throttle setting" (appearing as a singular control) and "heading angle" (appearing as a regular control). For a problem with state-inequality constraints and minimum time-fuel objective, we show that the optimal "heading angle" can be described through the classic Zermelo's navigation identity. We also demonstrate, by analyzing the switching function, that the singular "throttle setting" can be characterized through a feedback function that relies on both the optimal states and "heading angle". The switching-point algorithm is employed to solve a case study where we inspect the optimality conditions and graph the optimal controls together with the optimal state and co-state variables.
|
|
17:20-17:40, Paper FrC21.5 | |
>Propulsion-Free Cross-Track Control of a LEO Small-Satellite Constellation with Differential Drag |
|
Falcone, Giusy | Carnegie Mellon University |
Willis, Jacob B. | Carnegie Mellon University |
Manchester, Zachary | Carnegie Mellon University |
Keywords: Aerospace, Optimization, Autonomous vehicles
Abstract: In this work, we achieve propellantless control of both cross-track and along-track separation of a satellite formation by manipulating atmospheric drag. Increasing the atmospheric drag of one satellite with respect to another directly introduces along-track separation, while cross-track separation can be achieved by taking advantage of higherorder terms in the Earth’s gravitational field that are functions of altitude. We present an algorithm for solving a multisatellite formation flying problem based on linear programming. We demonstrate this algorithm in a receding-horizon control scheme in the presence of disturbances and modeling errors in a high-fidelity closed-loop orbital-dynamics simulation. Results show that separation distances of hundreds of kilometers can be achieved by a small-satellite formation in low-Earth orbit over a few months.
|
|
17:40-18:00, Paper FrC21.6 | |
>A Minimum-Propellant Pontryagin-Based Nonlinear MPC for Spacecraft Rendezvous in Lunar Orbit |
|
Bucchioni, Giordana | University of Pisa |
Alfino, Francesco | Politecnico Di Torino |
Pagone, Michele | Politecnico Di Torino |
Novara, Carlo | Politecnico Di Torino |
Keywords: Aerospace, Predictive control for nonlinear systems, Optimal control
Abstract: We propose a Nonlinear Model Predictive Control approach to spacecraft rendezvous in non-Keplerian Lunar orbits. The approach is based on the Pontryagin Minimum Principle and allows the accomplishment of minimum-propellant maneuvers. The relative motion between the chaser and the target is described by the nonlinear and unstable dynamics of the circular restricted three body-problem. In the proposed formulation, we design a minimum-propellant controller, which leads to a bang-bang behavior of the control signal. Under suitable assumptions, simplified dynamics is employed as prediction model, in order to reduce the complexity of the controller algorithm but, at the same time, without penalizing the controller tracking performance. The proposed approach's effectiveness is validated by a simulation example.
|
|
FrC22 |
Orchid Junior 4212 |
Time-Varying Systems |
Regular Session |
Chair: Liu, Shenyu | Beijing Institute of Technology |
Co-Chair: Sun, Zhiyong | Eindhoven University of Technology (TU/e) |
|
16:00-16:20, Paper FrC22.1 | |
>Online Learning Algorithms for Zero-Sum Games of Linear Systems Over Wireless MIMO Fading Channels with Uncountable State Space |
|
Tang, Minjie | The Hong Kong University of Science and Technology |
Lau, Vincent K N. | The Hong Kong University of Science and Technology |
Keywords: Time-varying systems, Game theory, Stochastic optimal control
Abstract: In this paper, we consider an online learning framework for a zero-sum game of an unstable linear dynamic system in the presence of wireless MIMO fading channels between the remote controllers and the actuator of the dynamic plant. We first formulate the stochastic zero-sum game as ergodic optimization problems, and propose a pair of equivalent reduced-state Bellman optimality equations to address the “curse of dimensionality” for Nash equilibrium of the game. Based on the reduced-state Bellman optimality equations, we analyze the structural properties of the Nash equilibrium and propose a novel low-complexity online stochasticapproximation(SA)-based algorithm to solve the reduced-state Bellman optimality equations. Numerical results are analyzed for the proposed learning scheme and several state-of-the-art learning approaches in terms of the computational complexity, the convergence performance as well as the robustness performance. We show that a significant performance gain can be achieved by the proposed scheme compared to the baseline approaches.
|
|
16:20-16:40, Paper FrC22.2 | |
>L_infty/L_2 Hankel Norm Analysis and Characterization of Critical Instants for Continuous-Time Linear Periodically Time-Varying Systems |
|
Hagiwara, Tomomichi | Kyoto Univ |
Yuyama, Taichi | Kyoto University |
Kim, Jung Hoon | Pohang Univeristy of Science and Technology |
Keywords: Time-varying systems, Linear systems, Computational methods
Abstract: This paper is concerned with the Hankel norm analysis of linear periodically time-varying systems with L_2 taken as the input space and the output regarded as an element in L_infty. An arbitrary Thetain[0,h) is first taken as the instant separating past and future, where h denotes the period of such systems, and what is called the quasi L_infty/L_2 Hankel norm at Theta is defined. Then, a computation method for the quasi L_infty/L_2 Hankel norm for each Theta is derived, and it is also shown that {it the} L_infty/L_2 Hankel norm defined as the supremum of the quasi L_infty/L_2 Hankel norms over Thetain[0,h) can be computed directly without dealing any quasi L_infty/L_2 Hankel norms. A relevant question of whether the supremum is attained as the maximum is also studied, in which case each maximum-attaining Theta is called a critical instant. In particular, it is discussed when and how the existenceslash absence of a critical instant (and all the values of critical instants, if one exists) can be determined without computing all (or any of) the quasi L_infty/L_2 Hankel norms over Thetain[0,h).
|
|
16:40-17:00, Paper FrC22.3 | |
>ISS of Rapidly Time-Varying Systems Via a Novel Presentation and Delay-Free Transformation |
|
Katz, Rami | Tel Aviv University |
Fridman, Emilia | Tel-Aviv Univ |
Mazenc, Frederic | INRIA-CENTRALESUPELEC |
Keywords: Time-varying systems, Lyapunov methods, Stability of linear systems
Abstract: We treat the input-to-state stability (ISS) of linear continuous-time systems with multiple time-scales. Such systems contain rapidly-varying, piecewise continuous and almost periodic coefficients with small parameters (time-scales). Our method relies on a novel delay-free system transformation in conjunction with a new system presentation, where the rapidly-varying coefficients are scalars that have zero average. We employ time-varying Lyapunov functions for ISS analysis. The analysis yields LMI conditions for ISS, leading to explicit bounds on the small parameters, decay rate and ISS gains. The novel system presentation plays a crucial role in the ISS analysis by allowing to derive essentially less conservative upper bounds on terms containing the small parameters. The obtained LMIs are accompanied by suitable feasibility guarantees. Numerical examples demonstrate the efficacy of the proposed approach in comparison to existing methods.
|
|
17:00-17:20, Paper FrC22.4 | |
>A Time-Varying Matrix Solution to the Brockett Decentralized Stabilization Problem |
|
Sun, Zhiyong | Eindhoven University of Technology (TU/e) |
Keywords: Time-varying systems, Stability of linear systems, Decentralized control
Abstract: This paper proposes a time-varying matrix solution to the Brockett stabilization problem. The key matrix condition shows that if the system matrix product CB is a Hurwitz H matrix, then there exists a time-varying diagonal gain matrix K(t) such that that the MIMO minimum-phase linear system is exponentially convergent. The proposed solution involves several analysis tools such as diagonal stabilization properties of special matrices, stability conditions of diagonal-dominant linear systems, and solution bounds of linear time-varying integro-differential systems. A review of other solutions to the general Brockett stabilization problem (for a general unstructured time-varying gain matrix K(t)) and a comparison study are also provided.
|
|
17:20-17:40, Paper FrC22.5 | |
>Online Data-Driven Adaptive Control for Unknown Linear Time-Varying Systems |
|
Liu, Shenyu | Beijing Institute of Technology |
Chen, Kaiwen | Imperial College London |
Eising, Jaap | University of California, San Diego |
Keywords: Data driven control, Time-varying systems, Stability of linear systems
Abstract: This paper proposes a novel online data-driven adaptive control for unknown linear time-varying systems. Initialized with an empirical feedback gain, the algorithm periodically updates this gain based on the data collected over a short time window before each update. Meanwhile, the stability of the closed-loop system is analyzed in detail, which shows that under some mild assumptions, the proposed online data-driven adaptive control scheme can guarantee practical global exponential stability. Finally, the proposed algorithm is demonstrated by numerical simulations and its performance is compared with other control algorithms for unknown linear time-varying systems.
|
|
17:40-18:00, Paper FrC22.6 | |
>Safe Control of Partially-Observed Linear Time-Varying Systems with Minimal Worst-Case Dynamic Regret (I) |
|
Zhou, Hongyu | University of Michigan |
Tzoumas, Vasileios | University of Michigan, Ann Arbor |
Keywords: Robust control, Time-varying systems, Optimal control
Abstract: We present safe control of partially-observed linear time-varying systems in the presence of unknown and unpredictable process and measurement noise. We introduce a control algorithm that minimizes dynamic regret, i.e., that minimizes the suboptimality against an optimal clairvoyant controller that knows the unpredictable future a priori. Specifically, our algorithm minimizes the worst-case dynamic regret among all possible noise realizations given a worst-case total noise magnitude. To this end, the control algorithm accounts for three key challenges: safety constraints; partially-observed time-varying systems; and unpredictable process and measurement noise. We are motivated by the future of autonomy where robots will autonomously perform complex tasks despite unknown and unpredictable disturbances leveraging their on-board control and sensing capabilities. To synthesize our minimal-regret controller, we formulate a constrained semi-definite program based on a System Level Synthesis approach for partially-observed time-varying systems. We validate our algorithm in simulated scenarios, including trajectory tracking scenarios of a hovering quadrotor collecting GPS and IMU measurements. Our algorithm is observed to have better performance than either or both the mathcal{H}_2 and mathcal{H}_infty controllers, demonstrating a Best of Both Worlds performance.
|
|
FrC23 |
Orchid Junior 4211 |
Sampled-Data Control |
Regular Session |
Chair: Zhang, Kuize | University of Surrey |
Co-Chair: Borri, Alessandro | CNR-IASI |
|
16:00-16:20, Paper FrC23.1 | |
>Data-Driven Output Feedback Control for Unknown Switched Linear Systems |
|
Hu, Kaijian | The University of Hong Kong, and HKU Shenzhen Institute of Resea |
Liu, Tao | The University of Hong Kong |
Keywords: Sampled-data control, Linear systems, Switched systems
Abstract: This paper proposes a data-driven control method to stabilize unknown switched linear systems under arbitrary switching. We consider the case where the system state is not measurable and design an output feedback controller only using measured input-output data. First, the system with multiple outputs is transformed into a single-output system with observability preserved. Then, a data-based state-space representation that has the same input-output relationship as the original system is constructed using the input-output data of the single-output system, based on which the data-driven controller is designed. Sufficient conditions for asymptotic stability of the closed-loop system under arbitrary switching are established in terms of linear matrix inequalities (LMIs). Compared with the existing method, the proposed method decreases the dimension of the constructed data-based state-space representation, which may reduce the computational burden of the controller design. The effectiveness of the proposed controller is illustrated by an example.
|
|
16:20-16:40, Paper FrC23.2 | |
>Constructing Feedback Linearizable Discretizations for Continuous-Time Systems Using Retraction Maps |
|
Jindal, Ashutosh | Indian Institute of Technology Bombay |
Banavar, Ravi N. | Indian Institute of Technology |
Martin de Diego, David | High Council for Scientific Research |
Keywords: Sampled-data control, Numerical algorithms, Feedback linearization
Abstract: Control laws for continuous-time dynamical systems are most often implemented via digital controllers using a sample-and-hold technique. Numerical discretization of the continuous system is an integral part of subsequent analysis. Feedback linearizability of such sampled systems is dependent upon the choice of discretization map or technique. In this article, for feedback linearizable continuous-time systems, we utilize the idea of retraction maps to construct discretizations that are feedback linearizable as well. We also propose a method to functionally compose discretizations to obtain higher-order integrators that are feedback linearizable.
|
|
16:40-17:00, Paper FrC23.3 | |
>Safe Digital Stabilization of Nonlinear Systems with an Application to Glucose Control |
|
Borri, Alessandro | CNR-IASI |
Di Ferdinando, Mario | University of L'Aquila |
Pepe, Pierdomenico | University of L' Aquila |
Keywords: Sampled-data control, Stability of nonlinear systems, Healthcare and medical systems
Abstract: In this paper, we propose a framework for the semiglobal practical safe stabilization of nonlinear continuous-time systems based on limited amount of information. This approach requires the availability of a continuous-time control law ensuring global asymptotic stability and a robust safety condition. Following an emulation-based approach, we introduce time sampling and quantizations on the input and state signals. We show that sufficiently high sampling frequency and small quantization error guarantee safety preservation and practical state stabilization to an arbitrarily small neighborhood of the origin while keeping the state within a safe region during the whole system evolution, which is essential in safety-critical applications. Numerical simulations on a glucose control problem in a non-ideal setting show the effectiveness of the approach.
|
|
17:00-17:20, Paper FrC23.4 | |
>A New Quasi-Finite-Rank Approximation of Compression Operators with Application to the L1 Discrtization for Sampled-Data Systems |
|
Kwak, Dohyeok | POSTECH |
Kim, Jung Hoon | Pohang Univeristy of Science and Technology |
Hagiwara, Tomomichi | Kyoto Univ |
Keywords: Sampled-data control, Optimal control, Time-varying systems
Abstract: This paper develops a new L1 discretization procedure for sampled-data systems, in which the minimization of the L∞-induced norm of sampled-data systems is concerned with. This discretization is based on developing a new quasi-finite-rank approximation (QFRA) of compression operators occurring from the lifting-based approach to sampled-data systems. More precisely, we develop a more sophisticated method for the QFRA of compression operators by using the idea of piecewise linear kernel approximation (PLKA) approach, rather than the conventional method based on the fastsample/fast-hold (FSFH) approach. The minimization problem for the corresponding QFRA error is shown to be solved through a linear programming (LP) problem. Furthermore, the theoretical effectiveness for the QFRA is established by deriving the associated convergence rate of 1/M, where M is the corresponding approximation parameter. This QFRA of compression operators leads to a new L1 discretization procedure for sampled-data systems. Finally, a numerical study is given to verify the effectiveness of the PLKA-based QFRA of compression operators together with its application to the L1 discretization of sampled-data systems.
|
|
17:20-17:40, Paper FrC23.5 | |
>Removing Two Fundamental Assumptions in Verifying Strong Periodic (D-)detectability of Discrete-Event Systems |
|
Zhang, Kuize | University of Surrey |
Keywords: Discrete event systems, Automata
Abstract: In this letter, in discrete-event systems modeled by labeled finite-state automata (LFSAs), we show new thinking on the tools of detector and concurrent composition and derive two new algorithms for verifying strong periodic detectability (SPD) without any assumption that run in NL; we also reconsider the tool of observer and derive a new algorithm for verifying strong periodic D- detectability (SPDD) without any assumption that runs in PSPACE. These results strengthen the NL upper bound on verifying SPD and the PSPACE upper bound on verify- ing SPDD for deadlock-free and divergence-free LFSAs in the literature. In our algorithms, the two assumptions are removed by verifying the negations of these properties.
|
|
17:40-18:00, Paper FrC23.6 | |
>Data-Driven Abstractions for Verification of Linear Systems |
|
Coppola, Rudi | Rudi Coppola |
Peruffo, Andrea | TU Delft |
Mazo Jr., Manuel | Delft University of Technology |
Keywords: Uncertain systems, Linear systems, Identification
Abstract: We introduce a novel approach for the construction of symbolic abstractions - simpler, finite-state models - which mimic the behaviour of a system of interest, and are commonly utilized to verify complex logic specifications. Such abstractions require an exhaustive knowledge of the concrete model, which can be difficult to obtain in real-world applications. To overcome this, we propose to sample finite length trajectories of an unknown system and build an abstraction based on the concept of l-completeness. To this end, we introduce the notion of probabilistic behavioural inclusion. We provide probably approximately correct (PAC) guarantees that such an abstraction, constructed from experimental symbolic trajectories of finite length, includes all behaviours of the concrete system, for both finite and infinite time horizon. Finally, our method is displayed with numerical examples.
|
|
FrC24 |
Orchid Main 4201AB |
Biologically-Inspired Methods |
Regular Session |
Chair: Li, Haitao | Shandong Normal University |
Co-Chair: Darlington, Alexander | University of Warwick |
|
16:00-16:20, Paper FrC24.1 | |
>Actuation and Flight Control of High-DOF Dynamic Morphing Wing Flight by Shifting Structure Response |
|
Sihite, Eric | Northeastern University |
Salagame, Adarsh | Northeastern University |
Ghanem, Paul | University of Maryland College Park |
Ramezani, Alireza | Northeastern University |
Keywords: Biologically-inspired methods, Simulation, Modeling
Abstract: Bat's dynamically morphing wings are highly versatile with many active and passive modes which allows them to display highly dexterous flight maneuvers. We take inspiration from bat wings and attempt to mimic their high degrees of freedom and flexibility in our small bat robot with dynamically morphing wings called the Aerobat. This small robot uses linkages, or computational structure, to animate the robot's flapping gait. In this work, we present the theoretical framework of using small low-energy actuators, called the primers, to adjust highly sensitive linkages length for changing the robot's flapping gait and use it to control the robot's orientation. This method is applied in a dynamic simulation to show its feasibility.
|
|
16:20-16:40, Paper FrC24.2 | |
>Fast Estimation of Morphing Wing Flight Dynamics Using Neural Networks and Cubature Rules |
|
Ghanem, Paul | University of Maryland College Park |
Erdogmus, Deniz | Oregon Graduate Institute, OHSU |
Ramezani, Alireza | Northeastern University |
Keywords: Biologically-inspired methods, Simulation, Modeling
Abstract: Fluidic locomotion of flapping Micro Aerial Vehicles (MAVs) can be very complex, particularly when the rules from insect flight dynamics (fast flapping dynamics and light wings) are not applicable. In these situations, widely used averaging techniques can fail quickly. The primary motivation is to find efficient models for complex forms of aerial locomotion where wings constitute a large part of body mass (i.e., dominant inertial effects) and deform in multiple directions (i.e., morphing wing). In these systems, high degrees of freedom yields complex inertial, Coriolis, and gravity terms. We use Algorithmic Differentiation (AD) and Bayesian filters computed with cubature rules conjointly to quickly estimate complex fluid-structure interactions. In general, Bayesian filters involve finding complex numerical integration (e.g., find posterior integrals). Using cubature rules to compute Gaussian-weighted integrals and AD, we show that the complex multi-degrees-of-freedom dynamics of morphing MAVs can be computed very efficiently and accurately. Therefore, our work facilitates closed-loop feedback control of these morphing MAVs.
|
|
16:40-17:00, Paper FrC24.3 | |
>Multi-UUV Dynamic Cooperative Task Planning Method Based on Multi-Objective Genetic Algorithm |
|
Luo, Naifu | Harbin Engineering University |
Wang, Hongjian | Harbin Engineering University |
Huang, Shuang | Wuhan Second Ship Design and Research Institute |
Gao, Wei | Harbin Engineering University |
Zhong, Bo | Harbin Engineering University |
Huang, Yutong | Harbin Engineering University |
Li, Benyin | Harbin Engineering University |
Keywords: Evolutionary computing, Optimization algorithms
Abstract: Aiming at the problems of scattered distribution, irregular shape, short underwater warning distance, limited carrying capacity of offshore islands and the inability for long term garrison, unmanned underwater vehicle (UUV) is used to search and explore the unknown underwater area near those islands. With the constraints on number of available UUVs, detection ability and energy consumption, a task planning framework of cooperative search and exploration mission of multi-UUV is urgently required. Meanwhile, in each round of task assignment, the most current algorithm could not dynamically assign the different task to corresponding UUV. For instance, the location and state of each UUV could be different during the searching and exploration process. In this paper, regarding the off-shore islands and reefs as the defense base, the models of UUV and its forward looking sonar are constructed, and a multi-UUV cooperative regional search and exploration algorithm is proposed based on multi-objective genetic algorithm (MGA). Aiming at the irregular distribution of targets in the search area and the different proportion of targets found by each UUV in their allocated search areas, we designed a multi-UUV dynamic cooperative (MDC) task planning method based on MGA to accomplish the multi-UUV dynamic scheduling. Finally, the underwater simulation environment is designed to simulate the distribution of offshore islands and reefs. The effectiveness of proposed MGA regional search and exploration algorithm and MDC-MGA task planning method is verified from the aspects of platform scale, time consumption and total distance of roadmap on regional search and exploration.
|
|
17:00-17:20, Paper FrC24.4 | |
>On the Implications of Controller Resource Consumption for the Long-Term Performance of Synthetic Gene Circuits |
|
Byrom, Daniel Peter | University of Warwick |
Darlington, Alexander P. S. | University of Warwick |
Keywords: Genetic regulatory systems, Biomolecular systems, Biotechnology
Abstract: Loss-of-function due to mutation presents a fundamental roadblock to the widespread application of engineered biological systems. The onset of mutations in synthetic gene regulatory networks creates parametric uncertainty while the resulting growth competition between mutant populations creates perturbations to the uptake of nutrients. Negative feedback is therefore an attractive strategy to extend the performance of gene circuits over evolutionary time. Here, we develop a mathematical model to evaluate the performance of a simple gene circuit within an evolving population. We show that negative feedback can improve evolutionary longevity. However, when we account for additional host resource consumption by the controller, this benefit can be reversed.
|
|
17:20-17:40, Paper FrC24.5 | |
>Approximation Method to Topological Structure and Stability Analysis of Large-Scale Boolean Networks (I) |
|
Li, Haitao | Shandong Normal University |
Yang, Xinrong | Shandong Normal University |
Li, Wenrong | Shandong Normal University |
Keywords: Stability of hybrid systems, Genetic regulatory systems, Large-scale systems
Abstract: This paper investigates the approximation problem of large-scale Boolean networks (BNs). The whole network is partitioned into several blocks and the input-output representation of each block is obtained via the observed data. By analyzing the simplified network composed of the input-output representation of each block, the properties of the original network can be obtained. The relations of topological structure and finite-time stability between the original system and the approximated system are discussed. Several illustrative examples are given to demonstrate the obtained results about the approximation of large-scale BNs.
|
|
17:40-18:00, Paper FrC24.6 | |
>Trajectory Generation Using Activator-Inhibitor Systems |
|
Al-Rawashdeh, Yazan Mohammad | Memorial University of Newfoundland |
Al Saaideh, Mohammad | Memorial University of Newfoundland |
Boker, Almuatazbellah | Virginia Tech |
Eldardiry, Hoda | Virginia Tech |
Heertjes, Marcel | Eindhoven University of Technology |
Al Janaideh, Mohammad | University of Guelph |
Keywords: Mechatronics
Abstract: It is once said that '{He who wishes to be obeyed must know how to command}.' Inspired by this saying, the dynamics of the partially known flexible motion system are considered in the making process of the desired trajectory signals it has to follow by exploiting systems and signals relations. Accordingly, the trajectory generator system activates the motion of the driven system whose tracking performance inhibits the generator and forces it to modify its trajectories while ensuring the desired motion requirements are met. Using singular perturbation theory, a near optimal trajectory generator system is designed, and with the aid of a suitable state observer a cascaded head-to-tail activator-inhibitor system configuration is realized. Essentially, the closed-loop error is fed-back to the trajectory generation process rather than using a limited feedforward controller alone based on the partially known dynamics. The superiority of the proposed technique is compared to the Sine-Squared motion trajectory, and its performance is evaluated through simulation.
|
|
FrC25 |
Lotus Junior 4DE |
Control Practice and Education |
Regular Session |
Chair: Bhowmick, Parijat | Indian Institute of Technology Guwahati |
Co-Chair: Lesic, Vinko | Faculty of Electrical Engineering and Computing |
|
16:00-16:20, Paper FrC25.1 | |
>Street Lighting Optimal Dimming with Model Predictive Control |
|
Shaheen, Husam | University of Zagreb, Faculty of Electrical Engineering and Comp |
Gapit, Marina | University of Zagreb, Faculty of Electrical Engineering and Comp |
Martinovic, Ana | University of Zagreb Faculty of Electrical Engineering and Compu |
Lesic, Vinko | University of Zagreb, Faculty of Electrical Engineering and Comp |
Keywords: Control applications, Smart cities/houses, Optimal control
Abstract: Street lighting dimming is adjustable to current micro-location conditions such as weather, road and pavement traffic type and density. With the trade-off goals of energy savings and required lighting quality, it is suitable for optimization problem formulation. The paper proposes a model predictive control for optimal dimming of street lighting adjustable to micro-location conditions and multiple spatial points of interest. Simplified mathematical model of street lighting ray tracing is utilized to capture expected illuminance in various points of interest in a three-dimensional space. Power percentage of luminaires is optimized based on predicted micro-location data and with imposed gradual rate of change. A joint street-wise dimming profile is adjusted to several points of interest for each luminaire as a reference tracking problem for optimizing the light demand trade-off in critical points from safety aspect, user comfort from social aspect and minimizing the overall consumption. The algorithm is verified on the realistic annual simulation for a case study of Kralja Tomislava street in City of Sisak, Croatia. The results show the potential of 31.94% less consumption compared with the currently operating street lighting.
|
|
16:20-16:40, Paper FrC25.2 | |
>A Novel Control Approach Based on Projection Dynamics |
|
Fu, Zao | University of Groningen |
Cenedese, Carlo | ETH Zurich |
Cucuzzella, Michele | University of Pavia |
Kawano, Yu | Hiroshima University |
Yu, Wenwu | Southeast University |
Scherpen, Jacquelien M.A. | University of Groningen |
Keywords: Control applications
Abstract: In this paper, we analyze the shifted and Krasovskii passivity properties of two types of projection dynamics. Combining the properties of projection operators and Lyapunov stability theory, we confirm that the projection dynamics on the feasible set and tangent cone possess Krasovaskii and shifted passivity properties. To show the effectiveness of the proposed approach, we design a controller for the boost converters in a DC microgrid, satisfying predefined input constraints.
|
|
16:40-17:00, Paper FrC25.3 | |
>A Negative Imaginary Approach for Distributed Secondary Frequency Consensus Control of Networked AC Microgrids (I) |
|
Ganguly, Arijit | University of Engineering and Management Kolkata |
Ayele, Adino Worku | Indian Institute of Technology Guwahati |
Bhowmick, Parijat | Indian Institute of Technology Guwahati |
Lanzon, Alexander | University of Manchester |
Keywords: Emerging control applications, Cooperative control, Autonomous systems
Abstract: This paper applies Negative Imaginary (NI) systems theory to design a new Secondary Frequency Consensus (SFC) control scheme for an inverter-based AC microgrid powered by battery, PV cells, fuel cells or hybrid energy sources. A microgrid consists of many Distributed Generating (DG) units whose dynamics can be modelled by a set of nonlinear differential-algebraic equations. Each DG can be feedback-linearised into a single integrator system, which resembles the simplified frequency dynamics of a microgrid. A network of many such feedback-linearised DG units gives rise to a homogeneous NI multi-agent system (MAS). Interestingly, a single-integrator MAS, owing to be NI, can be conveniently stabilised by a distributed Strictly NI (SNI) controller depending only on the definiteness of the DC gain matrix of the controller. It also successfully achieves the consensus, resulting in frequency synchronisation among all DG units and the main grid. An in-depth Matlab simulation case study has been performed on a prototype microgrid system to test the performance of the proposed scheme.
|
|
17:00-17:20, Paper FrC25.4 | |
>Passivity-Based Conditions for Asymptotic Stability of Speed Control for Three-Phase and Dual Three-Phase Permanent Magnet Synchronous Motors |
|
Zurita-Bustamante, Eric William | Brandenburg University of Technology Cottbus - Senftenberg |
Rueda-Escobedo, Juan G. | National Autonomous University of Mexico |
Schiffer, Johannes | Brandenburg University of Technology |
Keywords: Electrical machine control, PID control, Output regulation
Abstract: In this paper, we present sufficient conditions for guaranteeing global asymptotic speed regulation for three-phase and dual three-phase permanent magnet synchronous motors. Contrary to standard cascade control design approaches, where the inner and outer controllers cannot be tuned separately, we derive conditions on the controllers gains that are independent of each other. This tuning method is possible thanks to decomposing the machine dynamics as a negative feedback interconnection of two subsystems. The provided conditions then ensure the passivity of each subsystem, which in turn guarantees the asymptotic stability of the closed-loop equilibrium.
|
|
17:20-17:40, Paper FrC25.5 | |
>A New Online Continuing Education Course on Control Engineering |
|
Maciejowski, Jan M. | University of Cambridge |
Keywords: Control education, Control courses, Computer-aided learning
Abstract: We describe an online `continuing education' course on Control Engineering for graduates of any branch of Engineering or other scientific discipline. The course runs mostly asynchronously over 8 weeks, with the expectation that each student will devote 7-9 hours per week to it. Initially, motivational material is presented in the form of examples of control systems and their benefits. The feedback structure is emphasised, but feedforward, cascade and multivariable structures are also discussed. Sensors and actuators are introduced, several examples of each being given. Mathematical analysis is introduced after a qualitative understanding of feedback has been established. Emphasis is given throughout the course to PID controllers, including their implementation and limitations, as well as approaches to tuning them. `Classical' frequency-domain analysis and design methods for SISO systems are presented and emphasised. Later parts of the course cover more advanced material such as state feedback, observers, and LQG controllers. More advanced material, including MPC, adaptive and robust control, is introduced very briefly. The course is assessed by graded assignments based on a nonlinear model of an industrial process. Students develop a working knowledge of {Matlab} and {Simulink} software during the course. Keywords: Continuing education, online course, mature students, control engineering.
|
|
17:40-18:00, Paper FrC25.6 | |
>CPM Academy: A Remote Platform for Teaching Current Topics in Connected and Automated Vehicles |
|
Mokhtarian, Armin | RWTH Aachen University |
Hegerath, Lucas | RWTH Aachen University |
Alrifaee, Bassam | RWTH Aachen University |
Keywords: Control education, Control laboratories, Autonomous vehicles
Abstract: Bridging the gap between expensive real-world testing and inaccurate simulations, self-driving labs provide new opportunities for education and research in the field of connected and automated vehicles (CAVs). However, self-driving labs also have limited accessibility, requiring either travel or replication.To overcome these limitations, the Cyber-Physical Mobility (CPM) Lab at RWTH Aachen University offers publicly available remote access (CPM Remote). CPM Remote is a web framework that provides an easy introduction to CAVs and, together with the connection to the physical lab, a direct reference to reality.However, simply providing a platform is usually not enough to engage users. Therefore, we presented an application example called CPM Olympics, which was developed for researchers. In this paper, we present a second application example called CPM Academy. It is tailored for practice-oriented education and therefore designed and developed for students.The CPM Academy follows a didactic approach with various gamification elements and features a level-like structure built around a realistic scenario in the form of a package delivery service. In this way, the CPM Academy enables the study of various current topics in the context of CAVs, including control engineering, motion planning, and decision making.In addition, automated feedback and benchmarking help to engage students and improve the algorithms developed. The CPM Academy is freely accessible and is already being used in a teaching course at RWTH Aachen University.
|