New Frontiers in Control Systems
December 6 - December 7, 2023
The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
January 1, 2024: Happy New Year! Selected highlights from the workshop are now available on page Highlights.
December 6, 2023: The confirmation of boat trip seat reservation was sent. Please refer to Boat Trip page for more information.
December 6, 2023: Workshop check-in will start at 8:45 am today (Dec. 6). Please proceed to the entrance of Lecture Theatre K for check-in and name tag collection.
December 2, 2023: Program at a Glance and Travel & Venue information are available.
December 2, 2023: Registration open, please use the link https://forms.gle/T3gMjaLJEVbz4p3o8 or scan the QR code to register. All participants must be registered. *Limited seats, first come first served.
November 29, 2023: The offical website for the workshop is now open!
Title: Some Open Questions in Scalability of Multi-Agent Dynamic Systems
Abstract: There has been much work in relation to multi agent systems over many years. Yet some fundamental issues seem very difficult to both formulate clearly, and solve. In this talk I will look at some examples and analysis for which I am not aware of a clean solution. This will start with questions such as: (i) does asymmetry “help” in improving networked control? (ii) can we extend frequency domain sensitivity trade-offs work from strings to networks? (iii) are there simple, rigorous bounds on algebraic connectivity of families of graphs formed recursively?
Richard H. Middleton received the Ph.D. degree in electrical engineering from the University of Newcastle, Callaghan NSW, Australia, in 1987. He was a Research Professor with the Hamilton Institute, The National University of Ireland, Maynooth, from 2007 to 2011and is currently a Professor with the University of Newcastle. His research interests include a broad range of control systems theory and applications, including robotics, control of distributed systems, and systems biology. Prof. Middleton was the Program Chair (CDC 2006), CSS Vice President Membership Activities, and Vice President Conference Activities. In 2011, he was the President of the IEEE Control Systems Society. He is a Fellow of IEEE, and a fellow of IFAC.
Title: A New Paradigm for Signals and Control
Abstract: Modern technology has induced the strong trend of replacing conventional analog processing techniques by digital counterparts. The versatility of digital processing gives us the impression of almighty power of handling real-world problems. However, the real story is not all that simple, and we are confronted with various practical limitations. Of particular importance is that of bandwidth. Namely, digital processing places an upper bound for the maximum frequency band that we can deal with. Examples abound: the limitation of 20kHz in compact disc recordings; the lack of resolution in image processing due to limited sampling rates; rejection of high-frequency disturbance that is beyond the so-called Nyquist frequency, and also many others. All these problems reduce to one generic problem, namely, how one can obtain suitable signal actions in spite of the limited resolution due to a finite sampling period. The celebrated Shannon sampling theory seems to negate this hope: it claims that there is an absolute upper bound for processing digital signals, namely the Nyquist frequency. In this talk, we will clarify that this conclusion hinges upon an presumptuous hypothesis on the nature of signals, and can be replaced by another hypothesis on a physical model of the class of signals we are dealing with. Based on such a signal model, we can develop a new technique of obtaining high frequency components beyond the Nyquist frequency. We will base this new theory on the H-infinity sampled-data control theory, and exhibit various striking applications in signal processing, and also the control of signals beyond the Nyquist frequency.
Yutaka Yamamoto received his B.S. and M.S. degrees in engineering from Kyoto University, Kyoto, Japan in 1972 and 1974, respectively, and the M.S. and Ph.D. degree in mathematics from the University of Florida, in 1976 and 1978, respectively. From 1978 to 1987 he was with Department of Applied Mathematics and Physics, Kyoto University. In 1987 he joined the Department of Applied Systems Science as an Associate Professor, and became a professor in 1997. He had been a professor at the Department of Applied Analysis and Complex Dynamical Systems, Graduate School of Informatics of Kyoto University until 2015. He is now Professor Emeritus of Kyoto University.
His research and teaching interests are in realization and robust control of distributed parameter systems, learning control systems, and sampled-data systems, its application to digital signal processing, with emphasis on sound and image processing.
He received Sawaragi memorial paper award in 1985, outstanding paper award of SICE in 1987 and in 1997, the best author award of SICE in 1990 and in 2000, the George S. Axelby Outstanding Paper Award in 1996, and the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology Prizes for Science of Technology in 2007. He received the IEEE Control Systems Society Distinguished Member Award in 2009, and the Transition to Practice Award of the Control Systems Society in 2012, as well as the ISCIE Best Industrial Paper Award in 2009. He received the Tateishi Prize of the Tateishi Science and Technology Foundation in 2015. He is a Fellow of the IEEE, IFAC and SICE. He served as President of the IEEE Control Systems Society for 2013. He served as vice President for Technical Activities of the CSS for 2005-2006, and as vice President for Publication Activities for 2007-2008. He was an associate editor of the IEEE Transactions on Automatic Control, Automatica, Systems and Control Letters, Mathematics of Control, Signals and Systems. He served as a Senior Editor for the IEEE Transactions on Automatic Control for 2010-2011. He also served as an organizing committee member of 35th CDC in 1996, MTNS91 in Kobe, and as a member of program committees of several CDC's. He was the chair of the Steering Committee of MTNS, served as General Chair of MTNS 2006. He is a past President of ISCIE of Japan.
Title: Generalisations of BP Algorithm for Distributed Estimation and Optimisation
Abstract: In this talk, we study several related distributed estimation and optimisation problems for large networked systems. These problems include distributed solution to linear systems, distributed convex optimisation, and distributed weighted least squares. We introduce some powerful distributed algorithms generalised from the classical statistical learning algorithm known as belief propagation (BP) algorithm or message-passing algorithm. These algorithms are efficient, scalable, and easy to implement. The optimality and convergence properties of the proposed algorithms will be studied.
Minyue Fu received his Bachelor's Degree in Electrical Engineering from the University of Science and Technology of China, Hefei, China, in 1982, and Master and Ph.D. degrees in Electrical Engineering from University of Wisconsin-Madison, USA in 1983 and 1987, respectively. From 1987 to 1989, he served as an Assistant Professor in the Department of Electrical and Computer Engineering, Wayne State University, USA. He joined the University of Newcastle, Australia, in 1989 and became a Chair Professor in Electrical Engineering in 2003. He joined the Southern University of Science and Technology in 2023. His current research interests include networked control systems, distributed estimation and control, high-precision control, and reinforcement learning. He has been an Associate Editor for the IEEE Transactions on Automatic Control, IEEE Transactions on Signal Processing, Automatica and Journal of Optimization and Engineering. He is a Fellow of IEEE, Fellow of IFAC, Fellow of Engineers Australia, and Fellow of Chinese Association of Automation.
Title: The Evolution of the Distributed Observer and Its Applications
Abstract: A typical multi-agent system is composed of a follower system consisting of multiple subsystems and a leader system whose output is to be tracked by the output of each subsystem of the follower. What makes the control of a multi-agent system interesting is that the control law needs to be distributed in that it must satisfy time-varying communication constraints. A special case of the distributed control is where all the subsystems of the follower can access the full information of the leader. For this special case, one can design, for each follower subsystem, a conventional control law based on the information of the leader and this follower subsystem. The collection of these conventional control laws constitutes the so-called purely decentralized control law for the multi-agent system. Nevertheless, the purely decentralized control is not feasible as it violates the communication constraints. In this talk, we will elucidate a framework for designing a distributed control law by cascading a purely decentralized control law and a so-called distributed observer for the leader system, which is a distributed dynamic compensator capable of estimating the information of the leader and transmitting the estimated information to each follower subsystem over the communication network of the multi-agent system. Such a framework has found its applications to a variety of problems such as consensus, flocking, formation, cooperative output regulation, distributed Nash equilibrium seeking, and so on. The core of this design framework is the distributed observer for the leader system, which was initiated in 2010 for dealing with the cooperative output regulation problem and has experienced three phases of developments. In the first phase, the distributed observer only aimed at estimating the state of the leader over the communication network assuming every follower subsystem knows the dynamics of the leader. In the second phase which started in 2015, the distributed observer was rendered the capability of estimating not only the state but also the dynamics of the leader over the communication network assuming that only the children of the leader know the information of the leader. Such a dynamic compensator is called an adaptive distributed observer for a known leader system. The distributed observer was further enhanced in 2018 for linear leader systems containing unknown parameters, thus entering its third phase of the development. Such a dynamic compensator is called an adaptive distributed observer for an unknown leader system as it not only estimates the state but also the unknown parameters of the leader. The talk will start with an overview on the development of the distributed observer and then highlight our ongoing effort on establishing the output-based adaptive distributed observer for an unknown leader system over jointly connected communication networks. The talk will end with some extensions and applications of the distributed observer.
Jie Huang studied Power Engineering at Fuzhou University from 1977 to 1979 and Circuits and Systems at Nanjing University of Science and Technology (NUST) from 1979 to 1982 for a Master degree. He completed his Ph.D. study in automatic control at Johns Hopkins University in 1990. After a year with Johns Hopkins University as a postdoctoral fellow and four years with industry in USA, he joined the Department of Mechanical and Automation Engineering, the Chinese University of Hong Kong (CUHK) in September 1995, and is now Choh-Ming Li Research Professor of Mechanical and Automation Engineering. His research interests include nonlinear control, networked multi-agent systems control, game theory, and guidance and control of flight vehicles. He has authored/co-authored four monographs and over 400 papers.
He was elected HKIE Fellow in 2017, CAA Fellow in 2010, IFAC Fellow in 2009, and IEEE Fellow in 2005, and is now a life fellow of IEEE.
Title: Venture into Distributed Optimization: A Control-Theoretic Frequency-Domain Perspective
Abstract: The design of optimization algorithms has long been a matter of art, and it calls for systematic development of methods in which algorithms can be analyzed, designed, and benchmarked with regard to their key attributes such as efficiency, complexity, and robustness. Driven by prospects of ubiquitous applications critical to civil infrastructures and industrial systems, distributed optimization, widely considered the backbone of today’s large-scale engineering systems and complex networks, has received in the recent years considerable and increasing interest. Distributed optimization problems are typically posed in a setting of multi-agent systems, and distributed algorithms are sought after with the aim to achieve a global, common goal shared by all agents while the individual agents also seek to fulfill their own objectives. In this talk I shall describe a control-theoretic, frequency-domain framework for the analysis and synthesis of distributed algorithms. Leveraged on the insights and the varieties of time-honored frequency-domain techniques, in particular those of robust and optimal control, we propose a general class of gradient-based distributed algorithms that can be characterized as an interconnected dynamical system consisting of a linear subsystem and a Lur’e type nonlinear component, which enables the analysis and synthesis of the algorithms from a robust control approach, facilitated by the circle criterion and the Zames–Falb theorem. By equating algorithm convergence with the absolute stability of the Lur’e system, the optimization of the algorithm convergence rate is recast as a Nevanlinna-Pick interpolation problem akin to one of H∞ optimal control. The solution to this latter problem leads to a variety of gradient-based algorithms of optimal and suboptimal convergence rates with algorithm complexity judiciously controlled.
Jie Chen holds the appointment of Chair Professor with the Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China. He received the B.S. degree in aerospace engineering from Northwestern Polytechnic University, Xian, China in 1982, the M.S.E. degree in electrical engineering, the M.A. degree in mathematics, and the Ph.D. degree in electrical engineering, all from The University of Michigan, Ann Arbor, Michigan, in 1985, 1987, and 1990, respectively. Prior to joining City University, he was with The University of California, Riverside, California from 1994 to 2014, where he was a Professor and served as Professor and Chair for the Department of Electrical Engineering. He has also held guest positions and visiting appointments with institutions in Australia, Chile, China, France, Germany, Japan, and Sweden. His main research interests are in the areas of linear multivariable systems theory, system identification, robust control, optimization, time-delay systems, networked control, and multi-agent systems. He is the author of several books, on subjects ranging from system identification to time delay systems, and to information-theoretic control and fundamental control limitations.
An elected Fellow of IEEE, Fellow of AAAS, Fellow of IFAC and a Yangtze Scholar/Chair Professor of China, Dr. Chen received US National Science Foundation CAREER Award, SICE International Award, and Natural Science Foundation of China Outstanding Overseas Young Scholar Award. He was an IEEE Control Systems Society (CSS) Distinguished Lecturer. He served the IEEE and IFAC communities in various capacities, including, as a member on the CSS Board of Governors and a CSS Chapter Activities Chair, and a member of the IFAC Technical Board. He also served on a number of journal editorial boards, as an Associate Editor and a Guest Editor for the IEEE Transactions on Automatic Control, a Guest Editor for IEEE Control Systems Magazine, an Associate Editor for Automatica, an Associate Editor and a Guest Editor for International Journal of Robust and Nonlinear Control, and the founding Editor-in-Chief for Journal of Control Science and Engineering. He presently serves on the editorial boards of International Journal of Robust and Nonlinear Control, and SIAM Journal on Control and Optimization. He routinely serves on program and organizing committees of international conferences, most recently as the General Chair of the 3rd IEEE Conference on Control Technology and Applications, and the International Program Committee Chair of the 16th IFAC Workshop on Time Delay Systems.
Title: Distributed Entrapping Control of Multi-Agent Systems with Bearing Measurements
Abstract: In this talk we consider distributed entrapping control of multi-agents systems based on bearing measurements. A time-varying entrapping formation with a prescribed shape is adopted, and such a formation allows agents to move even in restricted areas while still entrapping the target. A distributed entrapping control framework based on a leader-follower structure is developed, which includes formation shape observers, relative position estimators, and distributed controllers. It is shown that the stability of the resulting closed loop system is guaranteed if its so-called bearing observability conditions are satisfied. Since the entrapping formation is determined by the trajectories of the leaders, we further characterize the sufficient conditions on the trajectories of the leaders such that the bearing observability conditions of the closed-loop system are always satisfied, and the estimation errors and the formation tracking errors converge to zero asymptotically. Simulations verify the effectiveness of the proposed control framework.
Gang Feng received the B.Eng and M.Eng. Degrees in Automatic Control from Nanjing Aeronautical Institute, China in 1982 and in 1984 respectively, and the Ph.D. degree in Electrical Engineering from the University of Melbourne, Australia in 1992.
Professor Feng was a Lecturer/Senior Lecturer at University of New South Wales, 1992-1999. He has been with City University of Hong Kong since 2000, where he is now a Chair Professor of Mechatronic Engineering and the director of Centre for Robotics and Automation. He has received the IEEE Computational Intelligence Society Fuzzy Systems Pioneer Award, the IEEE Transactions on Fuzzy Systems Outstanding Paper Award, the Outstanding Research Award and President Award of City University of Hong Kong, Alexander von Humboldt fellowship, and several best conference paper awards. He is listed as a SCI highly cited researcher by Clarivate Analytics since 2016. His research interests include intelligent systems and control, networked control systems, and multi-agent systems and control.
Professor Feng is a fellow of IEEE. He has been an Associate Editor of IEEE Trans. Automatic Control, IEEE Trans. Fuzzy Systems, IEEE Trans. Systems, Man, & Cybernetics, Mechatronics, Journal of Systems Science & Complexity, Journal of Guidance, Navigation & Control, and Journal of Control Theory and Applications. He is also on the advisory board of Unmanned Systems.
Title: Small Gain, Small Phase, and Their Mixture
Abstract: In this talk, we will examine some recent progress in phase analysis of feedback systems. We will present an old necessary and sufficient small gain condition for closed-loop stability, which will be followed by a new necessary and sufficient small phase condition. We will then present a sufficient mixed gain/phase condition for closed-loop stability. Finally, we will speculate whether a necessary and sufficient mixed gain/phase condition can be obtained.
Prof. Li Qiu received his Ph.D. degree in electrical engineering from the University of Toronto in 1990. After briefly working in the Canadian Space Agency, the Fields Institute for Research in Mathematical Sciences (Waterloo), and the Institute of Mathematics and its Applications (Minneapolis), he joined Hong Kong University of Science and Technology in 1993 and worked there until very recently. In 2023, he started working in Southern University of Science and Technology, Shenzhen. Prof. Qiu’s research interests include system, control, optimization theory, and mathematics for information technology, as well as their applications in manufacturing industry and energy systems. He is also interested in control education and co-authored an undergraduate textbook “Introduction to Feedback Control” which was published by Prentice-Hall in 2009. He served as an associate editor of the IEEE Transactions on Automatic Control and Automatica. He was the general chair of the 7th Asian Control Conference, which was held in Hong Kong in 2009. He was a Distinguished Lecturer from 2007 to 2010 and was a member of the Board of Governors in 2012 and 2017 of the IEEE Control Systems Society. He was the founding chairperson of the Hong Kong Automatic Control Association and a vice president of Asian Control Association. He is a Fellow of IEEE and a Fellow of IFAC.
Title: Majorization in Bode Type Gain and Phase Integrals for MIMO Systems
Abstract: In SISO control system theory, the celebrated Bode type integral relations, including the gain integrals (sensitivity and complementary sensitivity) and phase integrals provide fundamental limitations on performance of feedback control. Recently, we discover majorization inequalities in MIMO Bode type gain integrals and phase integrals, giving new design constraints for multivariable feedback control systems. The majorization inequalities reveal limits on the evenness of individual gain (or phase) integrals. They also retain a variety of known MIMO Bode type integral constraints.
Dr. Wei Chen received the B.S. degree in engineering and the double B.S. degree in economics from Peking University, Beijing, China, in 2008. He received the M.Phil. and Ph.D. degrees in electronic and computer engineering from the Hong Kong University of Science and Technology, Hong Kong, China, in 2010 and 2014, respectively. He is currently an Assistant Professor in the Department of Mechanics and Engineering Science at Peking University. Prior to joining Peking University, he worked at KTH Royal Institute of Technology and University of California at Berkeley for postdoctoral research, and the Hong Kong University of Science and Technology as a Research Assistant Professor. His research interests include linear systems and control, networked control systems, phase theory, optimal control, smart grid, and network science.
Title: Plug-and-Play Abilities for Multi-Agent Systems
Abstract: Multi-Agent systems, which are interconnected individual agents aiming at fulfilling a coordinated task, are utilised in a multitude of application areas, including vehicle platooning, formation control, and smart grid applications. In these areas often systems consisting of a large number of individual agents are considered. Hence, the study of scalability of proposed systems is critical. Known issues that can occur are the loss of stability, consensusability or amplification of disturbances. The latter is commonly known as string instability within the field of vehicle platooning. Another important aspect in many of these areas is that the number of agents varies with time. That is agents need to be able to connect and disconnect from the network. In a practical setting these connection and disconnections should have little to no impact on the overall performance of the network system and should be executed easily and rapidly. This is known as Plug-and-Play ability. In this talk, we will look at this issue in relation to scalability properties and will focus on the communication topology and its critical role played.
Sonja Stüdli received her Bachelor’s degree in electrical engineering and her Master’s degree in mechanical engineering from the ETH Zurich, Switzerland in 2008 and 2011, respectively. She received her Ph.D. degree in electrical engineering from the University of Newcastle, Australia, in 2016. She is currently working at the University of Newcastle as a research academic in the School of Engeneering. Her research interests include multi-agent systems, networked control, vehicle platooning, load management, smart grid operations, and distributed control.
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* The workshop was supported by the Postgraduate Students Conference/Seminar Grant of the Research Grants Council, Hong Kong.