Recent Advances in Control and Optimization
A Workshop in Honor of Professor Frank Lewis’ 70th Birthday
Lihua Xie, Nanyang Technological University, Singapore
Ben M. Chen, Chinese University of Hong Kong, China
Guoqiang Hu, Nanyang Technological University, Singapore
Yan Wan, University of Texas at Arlington, USA
Time: 2:00–5:30pm, July 16, 2019
Venue: Cullen Suite
Speech by Professor Frank Lewis
Professor F. L. Lewis National Academy of Inventors. Fellow IEEE, InstMC, and IFAC Moncrief-O’Donnell Endowed Chair and Head, Advanced Controls & Sensors Group UTA Research Institute (UTARI), The University of Texas at Arlington, USA Qian Ren Thousand Talents Consulting Professor, Northeastern University, Shenyang, China
National Academy of Inventors. Fellow IEEE, InstMC, and IFAC
Moncrief-O’Donnell Endowed Chair and Head, Advanced Controls & Sensors Group
UTA Research Institute (UTARI), The University of Texas at Arlington, USA
Qian Ren Thousand Talents Consulting Professor, Northeastern University, Shenyang, China
Biography: F.L. Lewis: Member, National Academy of Inventors. Fellow IEEE, Fellow IFAC, Fellow AAAS, Fellow U.K. Institute of Measurement & Control, PE Texas, U.K. Chartered Engineer. UTA Distinguished Scholar Professor, UTA Distinguished Teaching Professor, and Moncrief-O’Donnell Chair at The University of Texas at Arlington Research Institute. Founding Member Mediterranean Control Association. Qian Ren Thousand Talents Consulting Professor, Northeastern University, Shenyang, China. Ranked at position 81 worldwide, 59 in the USA, and 3 in Texas of all scientists in Computer Science and Electronics, by Guide2Research. Bachelor's Degree in Physics/EE and MSEE at Rice University, MS in Aeronautical Engineering at Univ. W. Florida, Ph.D. at Ga. Tech. He works in feedback control, reinforcement learning, intelligent systems, and distributed control systems. Author of 7 U.S. patents, 410 journal papers, 426 conference papers, 20 books, 48 chapters, and 12 journal special issues. He received the Fulbright Research Award, NSF Research Initiation Grant, ASEE Terman Award, Int. Neural Network Soc. Gabor Award 2009, U.K. Inst. Measurement & Control Honeywell Field Engineering Medal 2009. Received AACC Ragazzini Education Award 2018, IEEE Computational Intelligence Society Neural Networks Pioneer Award 2012 and AIAA Intelligent Systems Award 2016. IEEE Control Systems Society Distinguished Lecturer. Project 111 Professor at Northeastern University, China. Distinguished Foreign Scholar at Chongqing Univ. China. Received Outstanding Service Award from Dallas IEEE Section, selected as Engineer of the Year by Ft. Worth IEEE Section. Listed in Ft. Worth Business Press Top 200 Leaders in Manufacturing. Received the 2010 IEEE Region 5 Outstanding Engineering Educator Award and the 2010 UTA Graduate Dean’s Excellence in Doctoral Mentoring Award. Elected to UTA Academy of Distinguished Teachers 2012. Texas Regents Outstanding Teaching Award 2013. He served on the NAE Committee on Space Station in 1995.
Revisit of LQG Control--A New Paradigm
Professor Xiang Chen
Department of Electrical and Computer Engineering
University of Windsor, Canada
Abstract: A new design paradigm is discussed in this talk which allows 2-Dimensional controller design to achieve performance complements without trade-off. In particular, a revisit of the classical LQG control is presented with the proposed new control structure, which is motivated by the famous Youla parameterization of all stabilizing controllers. It is shown that this new paradigm is not only able to automatically render the exact LQG control performance if there is no modeling mismatch for the plant, but also provide recovery, instead of compromise, of the optimal performance when the modeling error is present, noting that the compromise is normally seen in traditional mixed or multi-objective designs. It is also noted that the recovery of the robust performance is regulated by the ‘measured error size’ of the modeling mismatch, hence, resulting in less conservativeness of the control performance. An example is presented to validate the design expectations of the new paradigm.
Biography: Xiang Chen received M. Sc. and Ph. D. degree in system and control from Louisiana State University in 1996 and 1998. He held cross-appointed positions in Department of Electrical and Computer Engineering and Department of Mechanical, Automotive and Materials Engineering at the University of Windsor, Canada, and is currently a Professor in the Department of Electrical and Computer Engineering. He has made fundamental contribution to Gaussain filtering and control, control of nonlinear systems with bifurcation, networked control system, and optimization of field sensing network. He has also made significant contribution to industrial applications of control and optimization in automotive systems and in visual sensing systems for manufacturing through extensive collaborative research and development activities with automotive, robotics, and manufacturing industries. Some of the deliverables have been patented by relevant companies or transferred to technological products of relevant companies. He is currently a Senior Editor for the IEEE/ASME Transactions on Mechatronics, an Associate Editor for SIAM Journal on Control and Optimization, and Associate Editors for International Journal of Intelligent Robotics and Applications, Control Theory and Technology (English Version), and Unman Systems. He received the Award of Best Paper Finalist from 2017 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2017), the Award of Best Student Paper Finalist (as supervisor author) from 2015 ASME DSCC, the New Opportunity Awards from the Canadian Foundation of Innovation (CFI) and from the Ontario Centre of Excellence-- Materials and Manufacturing Ontario, as well as 4 times Research Awards from the University of Windsor. His research has been well supported by government agencies at both federal and provincial levels in Canada and from industrial companies in both Canada and USA. His current research interests include multi-objective complementary optimization and control of systems with complexities, optimization and control of field sensing network and field sensor based autonomous operations, graph-/game-theoretic approaches for complex networked systems, as well as control applications to automotive systems and autonomous networked robotic vehicles. He is a registered Professional Engineer in Ontario, Canada.
Distributed matrix optimization and computation of matrix equations
Professor Yiguang Hong
Chinese Academy of Sciences, China
Abstract: In this talk, we start with brief introduction of distributed optimization problems. Then we discuss design and analysis for some matrix optimization problem and computations of some well known matrix equations. We propose continuous-time distributed algorithms and convergence analysis for the problems over multi-agent networks, where each agent can only get access to its local information.
Biography: Yiguang Hong received his B.S. and M.S. degrees from Dept of Mechanics of Peking University, China, and the Ph.D. degree from the Chinese Academy of Sciences (CAS), China. He is currently a professor in Academy of Mathematics and Systems Science, CAS, and serves as the Director of Key Lab of Systems and Control, CAS and the Director of the Information Technology Division, National Center for mathematics and Interdisciplinary Sciences, CAS. His current research interests include nonlinear control, multi-agent systems, distributed optimization and game, machine learning, and social networks. Prof. Hong serves as Editor-in-Chief of Control Theory. He also serves or served as Associate Editors for many journals including the IEEE Transactions on Automatic Control, IEEE Transactions on Control of Network Systems, IEEE Control Systems Magazine, and Nonlinear Analysis: Hybrid Systems. He is a recipient of the Guang Zhaozhi Award at the Chinese Control Conference, Young Author Prize of the IFAC World Congress, Young Scientist Award of CAS, the Youth Award for Science and Technology of China, and the National Natural Science Prize of China. Also, he is a Fellow of IEEE.
An Exact Gradient-Free Distributed Optimization Method with Optimal Averaging Schemes
Professor Guoqiang Hu
School of Electrical and Electronic Engineering
Nanyang Technological University, Singapore
Abstract: This talk will present a gradient-free distributed algorithm to solve a set constrained optimization problem under a directed communication network. Specifically, at each time-step, the agents locally compute a so-called pseudo-gradient in replace of the derivative for the updates of the decision variables, which can be applied in the fields where the gradient information is unknown, not available or non-existent. As compared to most distributed optimization methods, the proposed algorithm does not require the weighting matrix to be doubly stochastic, which enables the implementation in the graphs that are not doubly stochasticable. Furthermore, different from the approximate convergence to the sub-optimal solution achieved by most gradient-free algorithms, the proposed algorithm is able to achieve the asymptotic convergence to the exact optimal solution. Moreover, to establish the exact convergence, existing optimization methods usually assume the step-size to be nonsummable but square-summable. In the proposed algorithm, we adopt an optimal averaging scheme that only require the step-size to be positive, non-summable and non-increasing, which increases the range of the step-size selection.
Biography: Guoqiang Hu joined the School of Electrical and Electronic Engineering at Nanyang Technological University, Singapore in 2011, and is currently a tenured Associate Professor, the Director of the Centre for System Intelligence and Efficiency (EXQUISITUS), and the Assistant Chair (Research) of the School of Electrical and Electronic Engineering. He was an Assistant Professor at Kansas State University, Manhattan KS, USA, from 2008 to 2011. He received the B.Eng. degree in Automation from the University of Science and Technology of China in 2002, the M.Phil. degree in Automation and Computer-Aided Engineering from the Chinese University of Hong Kong in 2004, and the Ph.D. degree in Mechanical Engineering from the University of Florida in 2007. His research focuses on analysis, control, design and optimization of distributed intelligent systems. More specifically, he works on distributed control, optimization and games, with applications to energy systems, building systems and multi-robot systems. He has published 82 journal papers including 52 IEEE Transactions papers and 9 Automatica papers, with SCI citation counts about 2200 times and SCI H-index 25 and with Google Scholar citation counts about 4000 times and H-index 33. He was a recipient of the Best Paper in Automation Award in the 14th IEEE International Conference on Information and Automation in 2017, a recipient of the Best Paper Award (Guan Zhao-Zhi Award) in the 36th Chinese Control Conference in 2017, and a recipient of the Early Career Teaching Excellence Award at Nanyang Technological University, Singapore, in 2015. He serves as Associate Editor for IEEE Transactions on Control Systems Technology, Technical Editor for IEEE/ASME Transactions on Mechatronics, Associate Editor for IEEE Transactions on Automation Science and Engineering, and Subject Editor for International Journal of Robust and Nonlinear Control. He served as General Chair for the 15th International Conference on Control, Automation, Robotics and Vision (ICARCV 2018), General Co-Chair for the 14th IEEE International Conference on Control and Automation (IEEE ICCA 2018) and Program Chair for the 12th IEEE International Conference on Control and Automation (IEEE ICCA 2016).
Output Consensus of Linear Multi-Agent Systems with Adaptive Event-Triggered Control
Professor Lu Liu
Department of Biomedical Engineering
City University of Hong Kong
Abstract: In this talk, the output consensus problem for heterogeneous linear multi-agent systems via event-triggered control will be presented. By introducing a dynamic compensator for each agent, a fully distributed event-triggered control strategy with an adaptive event-triggering mechanism is proposed. It is shown that under the proposed control strategy, all agents asymptotically achieve output consensus with intermittent communication in a fully distributed manner. Moreover, with the proposed event-triggering mechanism, Zeno behavior is strictly excluded for each agent. The proposed event-triggering mechanism is independent of any global information and avoids the continuous monitoring issue.
Biography: Dr. Lu Liu received her Ph.D. degree in 2008 in the Department of Mechanical and Automation Engineering, Chinese University of Hong Kong, Hong Kong. From 2009 to 2012, she was an Assistant Professor in The University of Tokyo, Japan, and then a Lecturer in The University of Nottingham, United Kingdom. After that, she joined City University of Hong Kong, Hong Kong, where she is currently an Associate Professor. Her research interests are primarily in networked dynamical systems, control theory and applications and biomedical devices. She received the Guan Zhaozhi Best Paper Award of the 27th Chinese Control Conference in 2008, the Shimemura Young Author Award of the 11th Asian Control Conference in 2017, the Zhang Si-Ying Outstanding Youth Paper Award of the 30th Chinese Control and Decision Conference, and the Best Paper Award the 13th World Congress on Intelligent Control and Automation in 2018.
Dr. Liu is an Associate Editor of IEEE Transactions on Cybernetics, Control Theory and Technology, Transactions of the Institute of Measurement and Control, and Unmanned Systems. She served in organizing committee or operating committee of several international Conferences including the Invited Session Chair of 2018 International Conference on Control, Automation, Robotics and Vision, Program Chair of 2017 IEEE International Conference on Control and Automation, International Liaisons of 2016 Chinese Control and Decision Conference, and the Invited Session Chair of 2016 IEEE International Conference on Control and Automation.
Cooperative Control of Heterogeneous Multi-agent Systems: from Linear Systems to Nonlinear Systems
Professor Rong Su
School of Electrical and Electronic Engineering
Nanyang Technological University, Singapore
Abstract: Multi-agent system theory has found many applications nowadays. So far cooperative control of linear homogeneous multi-agent systems has been well studied. Yet, for heterogeneous systems, it is still a challenge. In this talk I will briefly describe some past and ongoing works on cooperative control of leader-follower heterogeneous systems. I will start with tracking, disturbance rejection and multiparty synchronisation of linear heterogeneous multi-agent systems that rely on solving output regulation equations in a distributed control architecture. After that, I will add a certain degree of nonlinearity in agent dynamics and discuss cooperative control of nonlinear heterogeneous multi-agent systems. In contrast to solving output regulation equations, here we explore the dynamics of system equilibrium points in three consecutive scenarios, i.e., a leader without an input, a leader with a bounded input, and a leader with an unknown dynamic input, and design distributed controllers accordingly. To gauge the influence of the equilibrium points, we develop a distributed error estimation framework. And to dynamically estimate and compensate the impact of leader's dynamics on each follower, we further investigate a synchronization problem, which is solved with distributed observers and dual design techniques. Extensive simulation case studies on tracking and formation control have been carried out to show the viability of our proposed cooperative control techniques.
Biography: Dr Rong Su obtained his Bachelor of Engineering degree from University of Science and Technology of China in 1997, and Master of Applied Science degree and PhD degree from University of Toronto in 2000 and 2004, respectively. He was affiliated with University of Waterloo and Technical University of Eindhoven before he joined the School of Electrical and Electronic Engineering at Nanyang Technological University in 2010. Dr Su's research interests include multi-agent systems, discrete-event system theory, model-based fault diagnosis, control and optimisation for complex systems with applications in flexible manufacturing, intelligent transportation, human-robot interface, power management and green buildings. In the aforementioned areas he has more than 180 journal and conference publications, 1 granted US patent, 1 granted Singapore patent, and has been involved in several projects sponsored by Singapore National Research Foundation (NRF), Singapore Agency of Science, Technology and Research (A*STAR), Singapore Ministry of Education (MoE), Singapore Civil Aviation Authority (CAAS) and Singapore Economic Development Board (EDB). Dr Su is a senior member of IEEE, and an associate editor for Automatica, Journal of Discrete Event Dynamic Systems: Theory and Applications, and Journal of Control and Decision. He is also the Chair of the Technical Committee on Smart Cities in the IEEE Control Systems Society.
Minimum Number of Switchers for Reachability of Switched Linear Systems
Professor Zhendong Sun
Chinese Academy of Sciences, China
Abstract: For both continuous-time and reversible discrete-time switched linear systems, it is well recognized that the controllability/reachability set is a subspace of the total state space. However, the problem of finding minimum number of switches for achieving reachability is still largely open. In this talk, we briefly introduce our very recent work that solves the problem in a general setting. The results could be extended to exploring minimum number of switches for observability/reconstructibility.
Biography: Zhendong Sun is a Researcher with the Key Laboratory of Systems & Control, Academy of Mathematics & Systems Science, Chinese Academy of Sciences. His research interests are in the fields of nonlinear control systems, switched and hybrid systems, and nano-micro-electronic systems. He is the first author of the monographs ``Switched Linear Systems-Control and Design'' and "Stability Theory of Switched Dynamical Systems (London: Springer, 2005 & 2011). He served/serves as Associate Editor for IEEE Transactions on Automatic Control and International Journal of Robust and Nonlinear Control.
Cyber-physical System Co-Design for UAV Networks
Professor Yan Wan
University of Texas at Arlington, USA
Abstract: UAVs, aerial robots with integrated sensing, communication, control, computing, and networking capabilities, are becoming part of the future IoT and Smart City networks. To address a variety of challenges for UAVs at vehicle and network levels, there are rich cyber-physical system co-design opportunities. In this talk, we will discuss several problems of recent interest include communication and control co-design for long-distance UAV communication, balance between on- and off-board operations, connection of local autonomy with global airspace capacity, heterogeneous multi-UAV coordination using distributed Reinforcement Learning and Bayesian Graphical Games, and probabilistic spatiotemporal scenario data-driven UAV traffic management.
Biography: Dr. Yan Wan is currently an Associate Professor in the Electrical Engineering Department at the University of Texas at Arlington. She received her Ph.D. degree in Electrical Engineering from Washington State University in 2009 and then postdoctoral training at the University of California, Santa Barbara. Her research interests lie in the modeling, evaluation and control of large-scale dynamical networks, cyber-physical system, stochastic networks, decentralized control, learning control, networking, uncertainty analysis, algebraic graph theory, and their applications to UAV networking, UAV traffic management, epidemic spread, complex information networks, and air traffic management. She received research grants from NSF, ONR, NIST, IEEE, Ford, Lockheed, and MITRE Corporation as subcontracts from FAA. Her research has led to over 150 publications and successful technology transfer outcomes. She has been recognized by several prestigious awards, including the NSF CAREER Award, RTCA William E. Jackson Award, U.S. Ignite and GENI demonstration awards, IEEE WCNC and ICCA Best Paper Awards, UTA STARS Award, UNT Early Career Award for Research and Creativity, and Tech Titan of the Future – University Level Award. She serves as the Associate Editor for IEEE Transactions on Control of Network Systems, Transactions of the Institute of Measurement and Control, and Journal of Advanced Control for Applications. She also serves as a Conference Editorial Board Member of the IEEE Control Systems Society, Vice President for IEEE ComSoc Fort Worth Chapter, and Technical Committee Member of AIAA Intelligent Systems, IEEE CSS Nonlinear Systems and Control, and IEEE CSS Networks and Communication Systems.
Asynchronous Distributed Optimization in Directed Networks
Professor Keyou You
Department of Automation
Tsinghua University, China
Abstract: A popular asynchronous protocol for distributed optimization is randomized gossip where a pair of neighbors concurrently update via pairwise averaging. In practice, this creates deadlocks and is vulnerable to information delays. It can also be problematic if a node is unable to response or has only access to its private-preserved local dataset. To address these issues simultaneously, we propose an distributed algorithm with directed communication where each node updates asynchronously and independently of any other node. If local functions are strongly-convex with Lipschitz-continuous gradients, each node converges to the same optimal solution at a linear rate of O(λ^k) , where the virtual index k increases by 1 no matter on which node updates. The superior performance is validated on a logistic regression problem against state-of-the-art methods in terms of linear speedup and implementations.
Biography:Keyou You received the B.S. degree in Statistical Science from Sun Yat-sen University, Guangzhou, China, in 2007 and the Ph.D. degree in Electrical and Electronic Engineering from Nanyang Technological University (NTU), Singapore, in 2012. After briefly working as a Research Fellow at NTU, he joined Tsinghua University in Beijing, China where he is now a Tenured Associate Professor in the Department of Automation. He held visiting positions at Politecnico di Torino, The Hong Kong University of Science and Technology, The University of Melbourne and etc. His current research interests include networked control systems, distributed algorithms and learning, and their applications. Dr. You received the Guan Zhaozhi award at the 29th Chinese Control Conference in 2010 and a CSC-IBM China Faculty Award in 2014. He was selected to the National 1000-Youth Talent Program of China in 2014 and received the National Natural Science Fund for Excellent Young Scholars in 2017.
Bearing-only formation tracking control of multiagent systems
Professor Shiyu Zhao
Westlake University, China
Abstract: The problem of distributed formation control of multiagent systems with limited sensing capabilities is a practical challenge motivated by incomplete and imperfect sensing. This talk addresses an important case where each agent in a network can sense only the relative bear¬ings to their nearest neighbors. The study of this topic is motivated mainly by the rapid development of bearing-only sensors, such as optical cameras and sensor arrays. In this talk, a recently developed bearing rigidity theory, which defines a necessary architectural feature of multiagent systems aiming to solve bearing-only formation control, is presented. Then, our recent research result on formation tracking using bearing measurements will be introduced.
Biography: Shiyu Zhao is an Assistant Professor in the School of Engineering and the Principle Investigator of the Intelligent Unmanned Systems Laboratory at Westlake University, China. He received the B.E. and M.E. degrees from Beijing University of Aeronautics and Astronautics in 2006 and 2009, respectively. He obtained the Ph.D. degree in Electrical Engineering from the National University of Singapore in 2014. From 2014 to 2016, he served as post-doctoral researchers at the Technion - Israel Institute of Technology and University of California at Riverside. From 2016 to 2018, he was a Lecturer in the Department of Automatic Control and Systems Engineering at the University of Sheffield, UK. He currently serves as an associate editor of Unmanned Systems and a number of international conferences such as IEEE ICCA, IROS, ICUAS, and ICARCV. He is a corecipient of the Best Paper Award (Guan Zhao-Zhi Award) in the 33rd Chinese Control Conference in 2014. His research interests lie in the area of intelligent and network robotic systems.
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