Ⅰ
Time: 10:00-11:00 am, Nov. 17, 2021
Tencent ID: 953 316 593
Theme: Distributed Nash equilibrium seeking over jointly connected switching networks
Abstract
The existing results on distributed Nash equilibrium seeking are obtained under the assumption that the communication network of the game players is either static and connected or switching but every time connected. In this talk, we will present an approach to deal with the distributed Nash equilibrium seeking over jointly connected switching networks. Such networks can be directed and disconnected at every time instant. The result includes the existing results as special cases.
Speaker: Prof. 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. After 4 years with NUST as a faculty member, he went to the Johns Hopkins University in 1986 and completed his Ph.D. study in automatic control there 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, CUHK. His research interests include nonlinear control, robotics and automation, networked control, and guidance and control of flight vehicles. He has authored/co-authored four monographs and some papers. He was elected HKIE Fellow in 2017, CAA Fellow in 2010, IFAC Fellow in 2009, and IEEE Fellow in 2005.
Ⅱ
Time: 11:00-12:00 am, Nov. 17, 2021
Tencent ID: 953 316 593
Theme: Remote State Estimation with Enhanced Robustness in the Presence of Data Packet Dropouts
Abstract
In this talk, a new robust filtering design is first presented driven by the residual signal related to the modeling mismatch. This new design framework is then applied to develop a remote state estimation mechanism over unreliable links, where the packet dropouts occur from the sensor side to the filter, for discrete-time systems with both bounded-power disturbances and white Gaussian noises. Through the adjoint operator, the estimation gains are characterized by two modified algebraic Riccati equations (MAREs), together with a complete and rigorous stability analysis in the mean square (MS) sense. Necessary and sufficient conditions for the MS stability of the corresponding error dynamics are then given in terms of the data arrival rate and unstable poles of the plant. Moreover, the filtering strategy is expanded into the case of distributed estimation over lossy sensor networks, where each sensor locally constructs an estimate based on its own observation and on those collected from its neighbors, and the solution is again derived by MAREs. The corresponding necessary and sufficient conditions to the MS stability in the distributed case are also characterized by relationships between data arrival rates and the Mahler measure of the plant. Finally, an example is included to validate the presented design method.
Speaker: Prof. 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 H∞ 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 of automotive systems and visual sensing systems in 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, the Award of Best Student Paper Finalist (as supervisor author) from 2015 ASME DSCC, the New Opportunity Awards from the Canadian Foundation of Innovation and from the Ontario Centre of Excellence-- Materials and Manufacturing Ontario, and 4 times Research Awards from the University of Windsor. His research has been well supported by research funds from government agencies at both federal and provincial levels in Canada and from industrial companies in both Canada and USA. His current research interests include model-guided optimization and control of systems with complexities, graph-/game-theoretic approaches for complex networked systems, control and optimization of field sensor networks for autonomous operations, as well as control applications to automotive systems and autonomous networked robotic vehicles. He is a registered Professional Engineer in Ontario, Canada.
