Keywords: Linear systems
Abstract: One of the most signicant areas emerging in the area of quantum technology is that of quantum computing. Companies such as Google, IBM, and Microsoft have made significant investments in quantum computing to develop small scale quantum computers using microwave frequency technologies involving arrays of superconducting Josephson junctions operating at millikelvin temperatures. Other technologies which have been investigated for the implementation of quantum computers include quantum optics, ion trap devices and solid state quantum technologies. Quantum amplifiers play a critical role in many of these quantum computing technologies in that they are required to read out qubit states and transfer the information to the classical world.

Quantum amplifiers are examples of linear quantum systems and can be analysed using the recently developed theory of quantum linear systems. We begin with an introduction to quantum linear systems theory including the concept of physical realizability. We then present a systems theory approach to the design of quantum amplifiers minimizing the amount of quantum noise introduced by the amplifier whilst still guaranteeing desired properties of the ampli fier such as the phase-insensitive property and the non-reciprocal property. We also consider the achievable gain and bandwidth of quantum amplifiers. These methods can be applied to amplifiers implemented using a quantum optics technology or a super-conducting microwave technology. Our approach is based on a singularly perturbed quantum system involving the broadband approximation of a Bogoliubov transformation. In the case the optical implementation of a phase-insensitive amplifier it requires two squeezers and two beamsplitters. In the case of the optical implementation of a non-reciprocal and phase-insensitive quantum amplifier it requires three squeezers and two beamsplitters.

Keywords: MEMS and nanotechnology
Abstract: Wafer scanners are complex lithography machines that are critical to the production of integrated circuits (or chips). Driven by the constant need to improve performance in terms of throughput, overlay, focus, and imaging, which can be linked directly to Moore’s law, the control design of wafer scanners is pushed to the limit. In this sense, inherent design limitations in linear feedback control have provided the motivation to explore nonlinear strategies. This is exemplified by the recent developments in hybrid integrator-gain systems, abbreviated with HIGS. By operating alternately in integrator mode or in gain mode, HIGS control has properties and associated (phase) benefits like reset control, in particular the Clegg integrator. However, HIGS does not produce discontinuous control signals due to the absence of (partial) state resets, which is considered a favorable property in dealing with structural dynamics of the wafer scanner, especially in the presence of weakly damped resonances. HIGS control offers the possibility to outperform linear controls and can benefit from the unstable control design of its underlying modes of operation. In the keynote lecture, an industrial nonlinear control perspective will be discussed that includes the following aspects: (a) inherent design limitations, (b) time- and frequency-domain stability tools, (c) robust nonlinear control design, and (d) nonlinear motion control performance.

Keywords: Mechatronic systems
Abstract: Digital printing and imaging systems are well-recognized mechatronics devices. They are an integral part of our daily lives. Although traditional print media has been in decline, recent interests in leveraging printing as a scalable fabrication/manufacturing process has renewed the development of functional printing as an additive manufacturing process. In addition to deposit precisely controlled amount of material with the necessary spatial accuracy, interaction between material and substrate as well as material with themselves all contribute to the geometry, functionality and quality of the final product, be it an image, device or structure. In this talk, I will present our experiences in applying different mechatronic techniques to several digital printing and imaging processes as well as sharing some insights gained when translating these approaches to other applications with similar implementation and real-world constraints.

Keywords: Power systems
Abstract: Wind energy is among the fastest-growing sources of electrical energy worldwide. Compared to land-based wind energy, offshore wind energy has the advantages of increased wind resource availability and consistency, proximity to major population centers, and enabling larger-scale turbines. As such, over the last decade, installed offshore wind power capacity has grown at a phenomenal average annual rate of 33%. Currently, more than 99% of installed offshore wind capacity consists of fixed-bottom wind turbines in shallow waters (<60m deep). Globally, however, 80% of offshore wind resources are at water depths greater than 60m. For such deep waters, floating offshore wind turbines are expected eventually to be as economically competitive as shallow-water fixed-bottom wind turbines. Basic types of floating wind substructures have been derived from platforms used in the oil and gas industry and result in safe but bulky and expensive designs. A novel Ultraflexible Smart FLoating Offshore Wind Turbine (USFLOWT) concept that better optimizes the design of the floating platform may be able to lower the cost of energy for floating offshore wind turbines. This talk will outline how, as part of a large team, we are using a control co-design approach to develop the USFLOWT concept. We describe some of the control challenges and highlight initial controllers and performance results. We close by discussing ongoing and future research avenues for the growing floating offshore wind energy area.

Keywords: Complex networks
Abstract: How a decentralized network gets to the goal (a consensus value) can be as important as reaching the consensus value. While prior methods focus on rapidly getting to a new consensus value, maintaining cohesion, during the transition between consensus values or during tracking, remains challenging and has not been addressed. Maintaining cohesion is important, e.g., to maintain inter-vehicle spacing in connected automated transportation systems, alignment synchronization to help maintain formations during maneuvers of flocks and swarms in nature, to avoid damage due to large deformations when transporting flexible objects and to maintain formation of engineered networks such as satellites, unmanned autonomous vehicles and collaborative robots.

The challenge to maintain cohesion arises because information about the desired response (such as the desired orientation or speed of the agents) might be available to only a few agents in a decentralized framework. The desired-response information needs to be propagated through the network to other agents, which results in response-time delays between agents that are “close to” the information source and those that are “farther away.” The talk will present a delayed self reinforcement (DSR) approach, where each individual augments its neighbor-based information update using its previously available updates, to improve cohesiveness of the response during transitions. The advantages of the proposed DSR approach are that it only requires already available information from a given network to improve the cohesion and does not require network-connectivity modifications (which might not be always feasible) nor increases in the system’s overall response speed (which can require larger input). Results are presented that show substantial improvement in cohesion with DSR.

Keywords: Transportation systems, Distributed parameter systems, Observers
Abstract: This article develops a boundary observer for the estimation of congested freeway traffic states based on the Aw–Rascle–Zhang (ARZ) partial differential equations (PDEs) model. Traffic state estimation refers to the acquisition of traffic state information from partially observed traffic data. This problem is relevant for freeway due to its limited accessibility to real-time traffic information. We propose a model-driven approach in which the estimation of aggregated traffic states in a freeway segment is obtained simply from the boundary measurement of flow and velocity without knowledge of the initial states. The macroscopic traffic dynamics is represented by the ARZ model, a 2 × 2 coupled nonlinear hyperbolic PDEs for traffic density and velocity. Using the PDE backstepping method, we construct a boundary observer consisting of a copy of the nonlinear plant with output injections from boundary measurement errors. The exponential stability of the estimation error system in the L2 norm and finite-time convergence to zero is guaranteed. Numerical simulation and data validation are conducted to validate the boundary observer design with vehicle trajectory data.

Keywords: Automotive applications, Cooperative control, Optimization
Abstract: In this paper we present a systematic approach for fuel-economy optimization of a connected automated truck that utilizes motion information from multiple vehicles ahead via vehicle-to-vehicle (V2V) communication. Position and velocity data collected from a chain of human-driven vehicles is utilized to design a connected cruise controller that smoothly responds to traffic perturbations while maximizing energy efficiency. The proposed design is evaluated using a high-fidelity truck model and the robustness of the design is validated on real traffic data sets. It is shown that optimally utilizing V2V connectivity leads to around 10% fuel economy improvements compared to the best non-connected design.

Keywords: Cooperative control, Automotive applications, Predictive control
Abstract: In this paper, we present a bilevel, model predictive controller for coordination of automated vehicles at intersections. The bilevel controller consists of a coordination level, where intersection occupancy timeslots are allocated, and a vehicle level, where the control commands for the vehicles are computed. We establish persistent feasibility and stability of the bilevel controller under some mild assumptions and derive conditions under which closed-loop collision avoidance can be ensured with bounded position uncertainty. We thereafter detail an implementation of the coordination controller on a three-vehicle test bed, where the intersection-level optimization problem is solved using a distributed Sequential Quadratic Programing method. We present and discuss results from an extensive experimental campaign, where the proposed controller was validated. The experimental results indicate the practical applicability of the bilevel controller and show that safety can be ensured for large positioning uncertainties.

Keywords: Linear robust control, Robotics applications, Game theory
Abstract: The robust linear tracking technique is applied to a practical path tracking problem for a ground vehicle modeled as a Dubins car. The tracking control is designed based on the optimal strategy in an auxiliary linear-quadratic differential game for a linearized vehicle model. In contrast with a purified theoretic setup, the real-life problem is complicated by a non-constant speed and control saturation. Moreover, the actual path generating control can be unknown to the tracking strategy designer. These issues required additional design blocks: speed tracking loop and leading angle differentiation, both based on similar tracking algorithms. The saturation effect is considered by using command reinforcement. Numerical and experimental results are presented and compared. Robustness with respect to unknown disturbances is demonstrated. Novel analytic results on the tracking error/control effort trade-off are also presented.

Keywords: PID control, Automotive applications, Identification
Abstract: This brief develops a method for system characterization and controller tuning for the boost control system of automotive turbocharged gasoline engines. The method utilizes the relay feedback technique for system characterization, followed by the internal model control (IMC) technique for controller tuning. The novelty is that instead of a high fidelity plant model, an ultra-simplified gain-integrator-delay model is employed in the IMC controller. As we show, our method leads to a time-efficient calibration process, assigns a desired closed-loop bandwidth exactly, and leads to good stability margins. A detailed and thorough analysis of the method, including its fundamental limitations, is provided. The method is experimentally applied to the boost control system of a turbocharged gasoline engine, where it is shown that the controller gains can be reliably computed at various engine operating points. The method identifies turbocharger speed as the best scheduling parameter for the controller gains, and the resulting controller is experimentally shown to yield good tracking performance.

Keywords: Power Electronics, Modeling, Energy Storage
Abstract: This paper aims at obtaining a suitable model of a Katium-power-converter-based battery charger, to further serve for control design purpose for railway applications. The Katium converter represents a particular DC-DC power converter topology. In the considered application a Katium converter operates as a Li-ion battery charger and a low-voltage power supply for a load composed of a resistive part and a constant-power part. Starting from the bilinear nature of the system model, a family of linear parameter-varying models is obtained by linearization around successive operating points, which mainly depend on the load power to be supplied. The modeling approach further relies upon the observation that the battery current regulation problem is a disturbance-rejection problem, where both constant and periodic disturbances act on the system. The obtained state-space model is validated by MATLAB®/Simulink® numerical simulation, providing a sound starting point for control strategy design.

Keywords: Power Electronics, Modeling, Health and medicine
Abstract: The power supply of a medical imaging system deals with a wide power range pulsed load. For a Vienna-type three-phase rectifier, the input current can therefore be in Discontinuous Conduction Mode (DCM) as well as in Continuous Conduction Mode (CCM). While Vienna modelling in CCM case and stability issues for a wide range of operating point have already been studied. A proper modelling for stability study in DCM case has not been made yet. A new linearised DCM model is presented and validated in this paper. DCM is shown more stable but more sensitive according to the operating point than CCM.

Keywords: Power Electronics, Optimization, Automotive applications
Abstract: To control static converters, several Pulse Width Modulation (PWM) was proposed. Their aim was to achieve a specific minimisation by choosing the inverter switching angles. Optimal pulse patterns could be obtained considering classic symmetries on a single leg. Also known as Quarter Wave Symmetry (QWS) , Half Wave Symmetry or Full Wave Symmetry (FWS). By this way the angles on each leg can be easily deduced from the solution of the first leg, it is also known that the harmonics multiple of three are systematically removed. In this work, any symmetry is considered and simulation results are provided according to this new strategy based on relaxation symmetry. Evaluation is done with four objectives functions Weighted Total Harmonic Distortion (WTHD) and three types of electric motor models. According to the models, the new strategy is compared to the case where the symmetries (QWS,HWS and FWS) are considered. In the motor models is computed efficiency, which includes switching and conduction losses inside the legs of the inverter. Models and methods was evaluated in simulation with arbitrary parameters.

Keywords: Power systems, Energy Storage, Optimization
Abstract: The increasing penetration of renewable energy sources in power grids highlights the role of battery energy storage systems (BESSs) in enhancing the stability and reliability of electricity. The application of decentralized control to improve the stability of a large-scale power system is inevitable, especially in distributed energy sources (DERs). A power grid is a strongly interconnected system; thus, the impact of each area on the decentralized control design needs to be taken into account. This paper presents an optimal distributed hybrid control design for the interconnected systems to suppress the effects of small distur- bances in the power system employing utility-scale batteries. The results show that the smart scheduling of the batteries’ output reduces the inter-area oscillations and improves the stability of the power systems.

Keywords: Power systems, Power Electronics, Predictive control
Abstract: In current Medium Voltage DC (MVDC) Shipboard Power Systems (SPSs), multiple sources exist to supply power to a common dc bus. Conventionally, the power management of such systems is performed by controlling Power Generation Modules (PGMs) which include fuel operated generators and underlying converters. Moreover, energy management is performed by the emerging single or hybrid Energy Storage Systems (ESSs). This paper presents a model and load predictive control framework for power and energy management of SPSs. Here, MPC with load prediction is used for three main objectives: (1) to request power and energy from generators and energy storage elements according to their individual State of Power (SOP) and ramp-rate limitations, (2) to consider and integrate the generator cost and degradation, and (3) to reach a specific parking (final) State of Charge (SOC) for the ESSs at the end of the prediction horizon. The solution of the optimization problem is demonstrated using MATLAB and the functionality of the control framework is validated in real-time simulation environment.

Keywords: Adaptive control, Power Electronics, Automotive applications
Abstract: This paper describes the influences of a voltage source inverter (VSI) on the acoustic behavior of a permanent magnet synchronous machine (PMSM), while it is used as an acoustic actuator. Two methods for compensating the nonlinear influences of the VSI are derived from the measurement results and are tested in a real-time environment. First, a static look-up table (LUT) is used to correct the duty cycle of the generated pulse-width-modulated (PWM) signal. At increasing excitation frequencies, the compensation quality decreases using the static LUT. Therefore, a second method, based on the wellknown filtered-x least-mean-square (FxLMS) is used to generate harmonic compensation signals.

Keywords: Marine/underwater robotics, Numerical analysis, Nonlinear systems
Abstract: Avoiding collisions is a crucial task for autonomous systems. Many strategies for avoiding obstacles have been proposed, yet the problem of having underactuated dynamics is rarely addressed in previous studies of collision avoidance algorithms. Underactuation of a system makes the collision avoidance control problem more complex, since the system then lacks the ability to directly control one or more of its degrees of freedom. Therefore, in this paper, we will consider collision avoidance for underactuated vehicles, specifically for the class of vehicles which cannot directly control their sideways speed. This is a broad class, which includes vehicles such as cars, airplanes, and marine vehicles. If the unactuated, sideways velocity component becomes sufficiently large, it can make the vehicle glide sideways rather than moving forward, which in the encounter with an obstacle may be fatal. To tackle this issue, we propose a reactive collision avoidance algorithm, based on the collision cone concept, which is specifically designed to account for the underactuated dynamics of a surface vehicle. We present a rigorous analysis of the closed-loop system, and establish explicit conditions guaranteeing vehicle safety. Simulations are included to verify the theoretical result.

Keywords: Robotics applications, Health and medicine
Abstract: This paper presents a new model and phase-variable controller for sit-to-stand motion in above-knee amputees. The model captures the effect of work done by the sound side and residual limb on the prosthesis, while modeling only the prosthetic knee and ankle with a healthy hip joint that connects the thigh to the torso. The controller is parametrized by a biomechanical phase variable rather than time and is analyzed in simulation using the model. We show that this controller performs well with minimal tuning, under a range of realistic initial conditions and biological parameters such as height and body mass. The controller generates kinematic trajectories that are comparable to experimentally observed trajectories in non-amputees. Furthermore, the torques commanded by the controller are consistent with torque profiles and peak values of normative human sit-to-stand motion. Rise times measured in simulation and in non-amputee experiments are also similar. Finally, we compare the presented controller with a baseline proportional-derivative controller demonstrating the advantages of the phase-based design over a set-point based design.

Keywords: Robotics, Cooperative control, Autonomous systems
Abstract: This paper presents a framework in which a group of nonholonomic wheeled mobile robots are cooperatively utilized to manipulate a polygonal object in the plane. In this framework, the robots are assumed to contact the object with- out friction, applying forces normal to the object’s boundary. Contacts between the wheeled mobile robots and object are resolved through Moreau’s time stepping algorithm with a linear complementarity problem. The robots are controlled so that the object’s pose is asymptotically stabilized without the need for trajectory planning. Lastly, a recovery controller is proposed that places agents on the boundary of the object with a force closure grasp. An extensive simulation study is presented to support the proposed framework.

Keywords: Robotics, Robotics applications, Control Technology
Abstract: Force Control in robotic manipulators generally requires the use of a relatively expensive F/T sensor to close the control loop. In recent years a trend to create low-cost robots arose and hence the need to reduce the use of expensive sensors i.e. avoid the use of a Force/Torque (F/T) sensor. In this work two disturbance observers are proposed for estimating the external forces (a disturbance) in parallel kinematic machines. In the paper, the external force is estimated through a Nonlinear Disturbance Observer and Extended Kalman Filter. The estimated force is used in a force controller with an inner position controller. It is shown that the estimated external force (contact force) can be estimated to an accuracy of 0.3 N and that it can be used for direct force control algorithms.

Keywords: Soft Robotics, Robotics applications, Predictive control
Abstract: With the ongoing digitalization of manufacturing, an increasing amount of production steps is carried out by robots. Typically they work autonomously, however so-called soft robots allow to further increase their interactivity with human workers. Yet, the modeling and control of such soft robots is still a relatively new research field. In particular, the accuracy and speed of the existing controllers is not adequate for industrial use. Therefore, this paper proposes the application of nonlinear model predictive control (NMPC) for a continuum manipulator as a special case of soft robotics. Successful experimental results are presented using the sequential quadratic programming real-time iteration (SQP-RTI) scheme for embedded optimization. The controller performance is superior to a nonlinear PD controller, which is used as a benchmark. In addition, the proposed NMPC allows to explicitly define state and input constraints on the manipulator, which can be exploited for further controller improvement in future work.

Keywords: Mechatronic systems, Linear systems, Predictive control
Abstract: Industrial cranes are usually driven manually by an operator setting the reference velocity of the drives using a handlever. Thereby, pendulum sway mainly occurs due to the input signal given by the operator and not due to external disturbances. In this paper, a feedforward controller based on trajectory generation for the payload velocity representing a flat output is presented. The trajectories for the flat output are calculated online using the handlever signal. Algebraic s-curve trajectories are planned in every time-step, which allows to consider velocity and acceleration limitations of the drives explicitly. The results are compared with the trajectories and feedforward control performance of a virtual model-predictive control loop. The latter is tuned such that the resulting trajectories are nearly time-optimal yielding a proper performancebenchmark. Both the flatness-based feedforward and the virtual model predictive control loop are tested in combination with a linear quadratic feedack regulator on a laboratory bridge crane.

Keywords: Fault detection/accomodation, Distributed parameter systems, Observers
Abstract: In this work, an adaptive observer is designed to detect a uniform electric long transmission line failure by considering a distributed parameter’s model where both voltage and current at the line ends are measurable. In particular, deterioration of the resistance R and conductivity G per-unit length are considered the parameters with abnormal conditions. To avoid numerical problems during the design and to generalize the results, the distributed system and the excitation are transformed into a dimensionless model before the estimation problem formulation. Based on this model, a distributed observer with boundary injections is designed. Thus, this observer’s output errors can be used as a residual generator for the detection of the resistance and conductivity deterioration. An adaptive observer is constructed by combining the distributed observer and a set of updating rules to identify the parameter deviations. A long transmission line is adopted as a case study to show the feasibility of the proposition for transmission line monitoring with two different generator signals in simulations.

Keywords: Kalman filtering, Communication networks, Real-time systems
Abstract: To reduce memory and computational effort, large-scale systems are often modeled globally and divided into local models with lower system order. In previous papers, local sensor-based systems are mostly manually distributed. In our contribution, the controllability and observability of the global system is considered and an extension from sensor nodes to sensor and actuator networks is performed. Therefore, the inputs and outputs of the global system are allocated to local systems. Here, the local systems are reduced by model order reduction methods. To further reduce the memory and computational effort, the estimation method is distributed in sensor and actuator nodes. When the sensor and actuator exchange state vectors in a fully connected communiaction network, the local systems represent the global system. Finally, the global system is reconstructed by a central fusion center. These methods are experimentally evaluated on a demonstrator.

Keywords: Fault-tolerant systems, Fault detection/accomodation, Renewable Energy
Abstract: This work presents an active fault-tolerant control (FTC) scheme by damping injection for a wave energy converter (WEC). The case study is an Archimedes wave swing-based WEC, where two braking subsystems for the floater play a critical role in protecting the physical structure from extreme sea conditions. In order to obtain fault-tolerant behavior in the presence of faults in the brakes, the deviation of the damping force is compensated through the force produced by the linear generator, which is controlled to maximize the energy conversion in nominal conditions. For this purpose, the force deviation is estimated from a fault detection and isolation (FDI) module by using an Utkin-based unknown input observer, which is then used for the compensation that completes the FTC. The proposed system is tested by numerical simulation under different scenarios, including faults in the damping system and others. The results demonstrate the capabilities and limitations of the proposal, which achieves the established objective. The performances of the nominal control and the proposed FTC are compared.

Keywords: Fault detection/accomodation, Stochastic/uncertain systems, Optimization
Abstract: This paper presents a fault detection algorithm based on moving horizon estimation (MHE) for uncertain nonlinear systems. Interval arithmetic is used to describe the unknown-but-bounded uncertainties that are present in practical systems. Based on this, a novel MHE problem is formulated which incorporates the uncertainties. Furthermore, an adaptive arrival cost approach is extended for the case of uncertain systems. The solution of this MHE problem provides an optimal estimate of the interval-valued states. Faults in the technical system will be detected on the basis of an intersection of the optimal interval-valued states with the uncertain measurements. Finally, the proposed fault detection algorithm is demonstrated using measured data of a nonlinear three-tank system.

Keywords: Kalman filtering, Control applications, Power systems
Abstract: This paper develops a fully distributed approach for implementing H_{infty} filtering over multi-agent networked systems. This is obtained by using diffusion techniques for the fusion of local filtering operations to enforce cooperation between agents and achieve a network-wide cohesive filtering operation. More importantly, we propose a diffusion-based algorithm which uses only locally observable states. Furthermore, the work includes the information formulation of the derived filtering framework. This information formulation not only provides the basis for the establishment of observability conditions but also allows for the extension of the derived filtering framework to nonlinear systems via the use of the unscented transform. Finally, the effectiveness of the derived estimation framework is demonstrated in two simulation examples.

Keywords: Neural networks, Fault detection/accomodation, Sensor fusion
Abstract: Industrial control systems provide transportation, essential utilities, and the manufacturing of goods to the masses. It is critical that controlled processes are executed correctly and according to schedule. Monitoring the system's performance during its operation is an important approach for maintaining high levels of reliability and availability. We present a system monitoring capability that implements parallel multi-view neural networks to detect anomalous behavior in an industrial control system by predicting operational states. By deploying the prediction capability within the system, system operation can be monitored in a semi-supervised manner to ensure the actual system state lies within an appropriate region of the state space that was previously predicted by the neural networks. Furthermore, if the two predictive models diverge in their classification of state (breaking consensus), it is likely that system operation has been compromised due to faulty equipment, communication errors, or some other source of malfunction. To achieve different ``views'' of the system, one predictive model is trained to analyze the data flow of system control packets and the other model is trained to analyze gyrometric signals obtained from physical sensors in the control system. We demonstrate that this methodology can detect anomalous behavior of an example industrial control system by emulating its operation in the presence of injected anomalies. Results indicate highly accurate anomaly detection during system operation.

Keywords: Health and medicine, Control applications, Real-time systems
Abstract: Ventilators are medical devices that provide respiratory life support for critically ill patients in the intensive care unit. While ventilators are widely addressed in the literature of critical care, the treatment of details surrounding control engineering as it applies to ventilators is significantly lacking compared to other control applications even though feedback control is the core technology empowering ventilator functionality.

Ventilators require precise and accurate control of flow, pressure, volume and gas oxygen concentration to meet all the clinical requirements to support safe and effective breath delivery. The performance of these controls depends on design and how well the design meets a challenging control imposed by nonlinear systems and constraints on how feedback is sensed and control is applied.

The purpose of this tutorial is to present the common problems ventilator control engineers need to solve and what controls are typically applied.

Keywords: Learning, Health and medicine, Nonlinear systems
Abstract: Mechanical ventilators sustain life of patients that are unable to breathe on their own. The aim of this paper is to improve pressure tracking performance of a nonlinear mechanical ventilation system using linear repetitive control, while guaranteeing stability. This is achieved by using feedback linearization and subsequently applying linear repetitive control to the linearized plant. The design procedure of this control strategy is developed in this paper. Thereafter, the controller is implemented in simulations and experiments showing superior pressure tracking performance of this control strategy compared to feedback control.

Keywords: Health and medicine, Modeling, Simulation
Abstract: Respiratory system modeling has been widely studied for a long time. Different types of models have been developed for different purposes. Review of the modeling literature reveals that there are two major motivations for the research in modeling of respiratory system. Physiologically based respiratory control system models get substantial academic attention in the fields of life sciences, physiology, and biomedical engineering. Those models attempt to include relevant physiological features for the purposes of study some specific aspects of the human respiratory systems. In this sense, a model that provides more details of the respiratory system related to blood gas exchange, metabolic activity, and brain neural central controller are mainly the focus.

Another motivation to model the respiratory system is driven by engineers and the developers of mechanical ventilators. In this field, the function of specific subsystems such as the lung mechanism is usually the focus, the whole respiratory system model is often reduced to its simplest configuration. For example, several models exist in the literature that commonly use an electrical circuit analogue to represent the pressure and airflow in the lung. However, these models usually lack the representation of physiological behavior of respiratory control systems and provide inadequate information for advanced mechanical ventilator systems development.

Modelling and simulation in engineering and in physiology have some common problems, although the disciplines may be very different for these two groups. As interests in the physiological closed-loop ventilators are increasing continuously, we expect that a closed-loop ventilator will help both patient treatments and clinician’s utilization of the machine. Therefore, it is interesting to bring more attention for ventilator engineers to study and integrate respiratory system models with physiological features into ventilator design and simulation. We believe this effort may bring some innovations in this field.

In this discussion, the use of MATLAB/Simulink program for modeling and simulation of the patient respiratory system and mechanical ventilation will be described.

Keywords: Game theory, Cooperative control, Robotics applications
Abstract: Potential games have some useful characteristics related to the existence and computability of their Nash equilibria, which make their use attractive also in the context of modelling interactions. This paper presents the use of potential differential games to model human-machine interaction. We extend the definition of static ordinal potential games to differential games for modelling and analysing human-machine interaction in the control of large vehicle-manipulators. We provide sufficient and necessary conditions for the existence of a potential differential game. In addition, we present an optimization formulation finding a linear-quadratic (LQ) potential differential game to a original game. The suitability of the proposed modelling approach is verified using simulation examples.

Keywords: Game theory, Cybersecurity, Communication networks
Abstract: In this paper we formulate a two-player game-theoretic problem on resilient graphs representing communication channels that are vulnerable to attacks in multiagent consensus setting. An attacker is capable to disconnect part of the edges of the graph by emitting jamming signals while, in response, the defender recovers some of them by increasing the transmission power for the communication signals over the corresponding edges. It is also possible for the attacker to emit stronger jamming signals that cannot be overcome by the defender. We consider repeated games where the utilities of players in each game depend on attack/recovery performance measured over multiple intervals. The utilities of both players are mainly related to agents' states and the cluster formation, i.e., how the agents are divided. The players' actions are constrained by their energy for transmissions, with a less strict constraint for the attacker compared to the defender. Numerical examples of dynamic games played over time are provided to demonstrate the cluster formation.

Keywords: Game theory, Learning, Optimization
Abstract: In this work, and inspired by the theory of bounded rationality and recursive reasoning, we propose two frameworks for modeling players' behaviors and for choosing their policies in multi-agent dynamic stochastic game settings. In particular, we define multiple levels of rationality for each player, where at each level a player may reason about everyone else in two different ways; first, they may assume that the rest of the players have a cognitive level that is immediately lower than theirs, which is known as level-k thinking; second, they may assume that the rest of the players' cognitive level follows a Poisson distribution, which is known as cognitive hierarchy. We construct algorithms for estimating the players' policies at each level of rationality, both in a level-recursive as well as in a level-paralleled manner, and we study these algorithms' convergence properties. Simulations on a grid world are provided to illustrate the efficacy of the proposed models.

Keywords: Game theory, Reinforcement learning, Automotive applications
Abstract: The focus of this paper is to propose a driver model that incorporates human reasoning levels as actions during interactions with other drivers. Different from earlier work using game theoretical human reasoning levels, we propose a dynamic approach, where the actions are the levels themselves, instead of conventional driving actions such as accelerating or braking. This results in a dynamic behavior, where the agent adapts to its environment by exploiting different behavior models as available moves to choose from, depending on the requirements of the traffic situation. The bounded rationality assumption is preserved since the selectable strategies are designed by adhering to the fact that humans are cognitively limited in their understanding and decision making. Using a highway merging application, it is demonstrated that the proposed dynamic approach produces more realistic outcomes compared to the conventional method that employs fixed human reasoning levels.

Keywords: Control applications, Control Technology, Nonlinear robust control
Abstract: Tokamaks are torus-shaped devices whose goal is to produce energy by means of thermonuclear fusion reactions. This is achieved by using helical magnetic fields to confine a plasma, i.e., a very hot ionized gas, so that the necessary conditions for fusion (i.e., high pressure and confinement time) are achieved. The safety factor is a measure of the pitch of the magnetic-field lines, and plays an important role in the magnetohydrodynamic stability and confinement properties of the plasma. In particular, the minimum value of the safety factor across the plasma spatial domain is often closely related to the maximum achievable plasma pressure. In this work, a robust, nonlinear, model-based controller for the regulation of the minimum safety factor is presented. The controller is synthesized via Lyapunov theory, and robustified against model uncertainties by means of Lyapunov redesign techniques. The controller is tested, together with a controller for the plasma thermal energy, in one-dimensional simulations using COTSIM (Control Oriented Transport SIMulator) for a DIII-D scenario.

Keywords: Sliding mode control, Actuators, Mechatronic systems
Abstract: Electrohydraulic systems, which have been widely used in a broad range of applications, are a typical nonlinear system with uncertainties. The presence of nonlinearities, parameter variations degrades the performance of linear controllers, such as the PID controller. As one of the most robust control strategies, sliding mode control methods attract the attention of researchers and are applied to electrohydraulic systems. However, for many fluid power applications, only the piston position measurement information is available. Owing to the existence of the nonlinear orifice dynamics, the observer design is a challenging task and satisfactory performance is not guaranteed in the existing literature. Therefore, an output feedback based high-order sliding mode control (HOSMC) design of electrohydraulic systems is proposed in this paper. By using an exact differentiator, the derivatives of the tracking error are obtained and used to construct the HOSMC. Compared to the conventional sliding mode control (SMC), the HOSMC can achieve a finite-time convergence and improved tracking accuracy. To verify the tracking performance, a simulation is performed on a camless engine valve actuation system.

Keywords: Sliding mode control, Adaptive control, Aerospace applications
Abstract: One solution to the problem of distributing the control action among redundant actuators with uncertain dynamics is employing an adaptive control allocator. This paper proposes a sliding mode controller which exploits a time-varying sliding surface to complement an adaptive control allocator in the presence of actuator saturation. The proposed approach does not require error augmentation for tracking desired references, which diminishes the computational burden. Aerodata Model in Research Environment (ADMIRE), which is an over-actuated aircraft model, is adopted to demonstrate the efficacy of the proposed controller in simulation studies.

Keywords: Sliding mode control, Aerospace applications, Nonlinear robust control
Abstract: This paper focuses on the design of the controllers for the release phase of the Test Masses (TMs) of the LISA (Laser Interferometer Space Antenna) mission. Space gravitational observatories such as LISA will be complementary in future years to existing terrestrial laboratories for detecting low-frequency gravitational signals that cannot be measured from Earth. TMs are used as sensors in science phase for environmental measurements; their control system must therefore be able to stabilize TMs with a limited control authority in spite of uncertainties and noises. In this paper, two sliding mode techniques are analysed and compared in terms of performance metrics, considering two operative modes and strict requirements in terms of accuracy and steady-state error. Extensive simulations are performed, taking into account a wide range of cases by varying noises and disturbances affecting the systems. In addition, the critical initial conditions of LISA Pathfinder (the previous mission) and their effects are analysed by using a nonlinear spacecraft dynamics.

Keywords: Sliding mode control, Cooperative control, Aerial robotics
Abstract: This paper proposes a fundamental sliding mode control (SMC) method for the formation of heterogeneous multi-agent systems with fixed topology and a virtual leader consisting of quadrotor unmanned aerial vehicles (UAVs) and two wheeled mobile robot (2WMR) unmanned ground vehicles (UGVs). SMC is used to direct the agents for the purposes of achieving consensus and formation in a two-dimensional plane. The stability analysis with the resultant system shows that the errors can be driven to zero in finite time. Finally, simulation results are shown to demonstrate the effectiveness of the proposed control scheme for a team of three quadrotors and three mobile robots. Both static and dynamic formation cases are validated with extensive simulated studies.

Keywords: Distributed parameter systems, Energy Storage, Nonlinear robust control
Abstract: This paper proposes a novel control algorithm of a thermal phase change process and shows its experimental verification using paraffin as a phase change material (PCM). The core problem is to design a boundary feedback control for the ``Stefan system" which describes a time evolution of the temperature profile in liquid phase which is associated with a time evolution of a position of liquid-solid phase interface, for the sake of stabilizing the interface position at a chosen setpoint. First, we design the continuous-time full-state feedback control law by means of PDE backstepping method, which in the absence of a demand for accelerated convergence can also be arrived at by energy-shaping method, and rigorously prove the stability of the closed-loop system under sufficiently small heat loss. Next, the control law is refined via an observer-based output feedback under sampled-data measurements of the surface temperature and the phase interface position so that the control algorithm is practically implementable. Then, we conducted an experiment under a constant input to calibrate unknown parameters involved with the heat loss. Finally, the proposed model-based boundary feedback control algorithm is implemented in the experiment of melting paraffin. The experiment was successful: the convergence of the phase interface to the setpoint was achieved.