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Abstract: The objective of this half-day workshop is to cover the state-of-the-art in smooth fuzzy modeling and control algorithms along their systemic properties and the applications. During the last years, we have witnessed major successes of fuzzy logic systems in the academia and industries. From beating professionals at games like chess, to fast detection of diseases like cancer, classification of complex images, and generation of captions for images in the personalized media of the incomplete and noisy information. In many AI fields, fuzzy systems could outperform all existing machine learning and model-based control methods. Three major aspects of fuzzy systems make the design methodology attractive. The first is the design formulation, that they can be understood, tuned, or improved by engineer’s experiences and knowledge. The second aspect is the ability to handle the system disturbances and noises soft and smoothly, which facilitate the operation of industrial processes inside their margins and operational limits. The third aspect is the ability to perform on-line decision making for the processes, considering their affordable computational complexities. Hence, the purpose of providing this workshop is to provide a detailed introduction to the fundamental developments in this field for researchers, graduate students and practitioners. The main focus of the course is on the design of smooth fuzzy models for various applications which include control, modelling, and self-learning for the dynamical systems, as well as the comprehensive study of the new achievement in study of their structural properties.

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Abstract: In this workshop, the theory, design, and applications of estimators for the states and unknown inputs of control systems will be presented in a tutorial fashion. The workshop targets both practicing engineers and graduate students. The emphasis will be on design in order to show how uncertain system control theory fits into practical applications. Observation and measurement play essential roles in achieving control objectives in many control schemes. An observer is a deterministic dynamical system that can generate an estimate of the plant’s states using that plant’s inputs and outputs. Observers are utilized to augment or replace sensors in a control system. The early observers required full knowledge of the inputs of the controlled plant. Observers that do not require full knowledge of the inputs have also been developed and are collectively called Unknown Input Observers (UIO). Some uncertainties, nonlinearities, and delays in the system model can be treated as unknown inputs. Methods for the estimation of the unknown inputs have been developed. One important application of UIOs of current interest is in secure state estimation of network control systems corrupted by malicious packet drops both in the communication between the sensors and the controller and that between the controller and the actuators. Another area of application of UIOs is fault detection and isolation, which is also one of the topics of this workshop. We will present an unknown input estimator architecture that reconstructs sensor and actuator faults. Novel robust discrete-time (DT) observer architectures will also be presented. We will demonstrate how these observers are used in the synthesis of combined controller-observer compensators for continuous-time (CT) systems. The advantage of the compensator synthesis in the DT domain over the CT domain is that in many cases the condition for the existence of an UIO fails for a CT plant model while it holds for a discretized plant model. We will characterize a class of systems for which the existence condition for the UIO fails in the CT domain while it holds in the DT domain.

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Abstract: This one-day workshop will focus on current control system topics that are having an impact in the aerospace industry. The workshop will be presented by leading control systems experts from industry and academia that are involved in some of the most exciting research and development efforts in the field of Aerospace. This workshop is intended for students and professors in search of current applications in need of solutions as well as industry and government professionals interested in potential solutions from academia and adjacent branches of the aerospace industry. This workshop is sponsored and presented by members of the IEEE CSS Technical Committee on Aerospace Controls and their collaborators. The purpose of the technical committee is to help build an international scientific community and promote awareness of outstanding achievements in the field of Aerospace Controls. In this offering, the workshop will present a sample of current topics related to the intelligent control of cooperating groups of unmanned air vehicles, spacecraft, drones and miniature projectiles. Our experts will present the theoretical background, rigorous methods and experimental results that are creating an exciting new chapter in field of Aerospace Control. Recent advances in adaptive and nonlinear robust control theory are used to form the basis for safe, resilient and certifiable systems of co-operative platforms. Future directions for research are included in discussion of the roles of artificial intelligence and augmented and virtual reality, as well as emerging applications in Aerospace Control for adversarially robust cyber resistant systems. The workshop will offer opportunities for questions and answers and provide an open forum for discussion of applications for current theoretical advances and potential enabling technologies.

Please see http://aerospace-controls.ieeecss.org/home for additional information and agenda, follow the tab to TCAC Workshop on Aerospace Control – 2020 ACC.

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Abstract: A question one should ask of any advanced algorithm is, “How do we make that work in a real system?” A question one should ask of any industrial control system is, “How do we apply better algorithms to this problem?” The two questions are dual sides of the same “bridging the gap” problem that has hounded control for decades. This workshop will examine practical methods that address this problem from both sides: ways to implement advanced algorithms on real systems and ways to improve industrial control using advanced methods. We will examine which system identification methods work on which physical systems, as model-based control requires a model. We will discuss why so many industrial controllers are PIDs, present a universal framework for different PID implementations, describe how to tune the PID to the identified system model, and show how to augment these with higher order controller dynamics (a.k.a. filters). We will discuss how to make state-space models more useable in real-time systems. Speaking of which, we will explain how to program filters and PIDs in real-time control systems. We will discuss things to know about hardware implementation and tradeoffs with ADCs, DACs, and analog filters. We will talk about the current set of real-time processing chips and the programming models that go along with them. Throughout we will offer hardware/software demonstrations of how tools like Matlab and Simulink can be used in these contexts. We won’t bridge the gap in a day, but we can move the needle. A web page that holds the information from the brochure can be found http://dabramovitch.com/practical_methods/ and a PDF version of the workshop flyer can be found http://dabramovitch.com/practical_methods/practical_methods_workshop_overview_2020.pdf

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Abstract: The use of visual sensors in feedback control has been an active topic of research for decades. As the cost of hardware lowers and computational capabilities increase, vision-based control is reaching new levels of capability and application. Recent innovations in computer vision can provide greater capabilities to control applications such as autonomous vehicles and robots. At the same time, open problems in computer vision can be solved through control theory, such as nonlinear and adaptive control. We present eleven discussions on recent work in vision-based control, the application of control to computer vision, and topics in which vision and control are uniquely intertwined. We seek to highlight recent developments and open problems that exist at the intersection of vision and control and spur further research and development in the community. Further information on the workshop can be found at https://sites.google.com/view/2020accworkshop

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Abstract: Two different perspectives of casting problems for finite dimensional nonlinear dynamical systems into infinite dimensional linear problems have been gaining significant traction over the past decade. Specifically, these two approaches are that of Dynamic Mode Decomposition (DMD), which aims to establish “equation-free” models from snapshots of a dynamical system by exploiting properties of the Koopman operators over Hilbert function spaces, and that of Liouville operators and occupation kernels, where nonlinear optimal control problems are reformulated as infinite dimensional linear programs. The purpose of this workshop is to bring together practitioners of both fields together to enable a unifying discourse concerning nonlinear dynamical systems and their connections to infinite dimensional spaces. The presentations will include topics such as DMD, moment problems, Reproducing Kernel Hilbert spaces, and Lyapunov measures. The workshop will conclude with several talks connecting DMD with Liouville operators using newly introduced occupation kernels. This workshop aims to provide a comprehensive treatment of Dynamic Mode Decompositions and moment problems using Occupation Measures. The attendees will leave with a thorough understanding of how to cast finite dimensional nonlinear problems into infinite dimensional linear problems and will understand this approach from multiple perspectives. Attendees who are already familiar with both methods will be introduced to occupation kernels and Liouville operators which can be leveraged to blend DMD with the theory of occupation measures via a Reproducing Kernel Hilbert Space framework.

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Abstract: Biomedical systems are notoriously difficult to model. This difficulty stems from the variation in physiology between subjects. Furthermore, an individual subject will often vary over the course of a day, a week, etc. This difficulty in modeling makes it difficult to implement optimal control solutions. Extremum Seeking Control (ESC) is a method of model-free adaptive control that modifies the arguments of a cost function to guide them to a local maximum or minimum. The versatility and model-free nature of ESC makes them very well suited for biomedical control applications. We will present nine recent results in applying ESC to a wide variety of biomedical problems, including powered prosthetics and orthotics, medication delivery, rehabilitation therapy, and assistive heart pumps. We seek to highlight the strengths of ESC in biomedical applications and spur further research and development in the community who may not have considered this powerful approach. The workshop will include an introductory session for those unfamiliar with ESC, and we will provide tutorial papers on the workshop webpage, https://sites.google.com/view/esc4biomed.

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Abstract: This one-day workshop will focus on major problems facing the design framework for autonomous vehicular and manufacturing operation, involving the following topics:

Modeling field sensing and perception such as visual, LIDAR, and soft sensor based on deformation and temperature field reconstruction, Smart actuator based on modular design and embedded field sensors, Visual sensor guided autonomous vehicular formation operations, Networked sensing and estimation for ground and underwater autonomous vehicular systems, Task-oriented autonomous unmanned aerial vehicular operations.

The presented talks by invited speakers are to provide updates of frontiers in these topics and to collectively present the design philosophy of task-oriented autonomous operations seen in vehicular and manufacturing systems.

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Abstract: Meeting: Board of Governors

https://ucsd.zoom.us/j/92703928027?pwd=UVNpQWdJWXc0dlpnWTFyQW5RQUpuZz09

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Abstract: ASME DSCD ExComm meeting

https://us02web.zoom.us/j/84816271700

Tuesday 1:30PM to 5:30 PM Session: TuWT2

Contact Meeting Organizer for Password

Keywords: Control applications
Abstract: In September 2015, the Laser Interferometer Gravitational-wave Observatory (LIGO) initiated the era of gravitational wave astronomy (a new window on the universe) with the first direct detection of gravitational waves (ripples in the fabric of space-time) resulting from the merger of a pair of black holes into a single larger black hole. In August 2017 the LIGO and VIRGO collaborations announced the first direct detection of gravitational waves associated with a gamma ray burst and the electromagnetic emission (visible, infrared, radio) of the afterglow of a kilonova — the spectacular collision of two neutron stars. This marks the beginning of multi-messenger astronomy. The kilonova discovery was made using the U.S.-based LIGO; the Europe-based Virgo detector; and 70 ground- and space-based observatories.

The Advanced LIGO gravitational wave detectors are second generation instruments designed and built for the two LIGO observatories in Hanford, WA and Livingston, LA. These two identically designed instruments employ coupled optical cavities in a specialized version of a Michelson interferometer with 4 kilometer long arms. Resonant optical cavities are used in the arms to increase the interaction time with a gravitational wave, power recycling is used to increase the effective laser power and signal recycling is used to improve the frequency response. In the most sensitive frequency region around 100 Hz, the displacement sensitivity is 10^-19 meters rms, or about 10 thousand times smaller than a proton. In order to achieve this unsurpassed measurement sensitivity Advanced LIGO employs a wide range of cutting-edge, high performance technologies, including an ultra-high vacuum system; an extremely stable laser source; multiple stages of active vibration isolation; super-polished and ion milled optics, high performance multi-layer dielectric coatings; wavefront sensing; active thermal compensation; very low noise analog and digital electronics; complex, nonlinear multi-input, multi-output control systems; a custom, scalable and easily re-configurable data acquisition and state control system; and squeezed light. The principles of operation, the numerous control challenges and future directions in control will be discussed. More information is available at https://www.ligo.caltech.edu/