报告题目：Cooperative Control Synchronization: Optimal Design and Games on Comunication Graphs

报 告 人： Lewis，Frank Leroy教授（The University of Texas at Arlington, USA）

报告时间：2017年5月10日 上午10：00

报告地点：南一楼中311

Abstract: The interactions of dynamical systems communicating over a networked environment lead to intriguing synchronization behaviors with applications in Internet of Things, formations, satellite control, and human societal behaviors. This talk studies the relation between local controls design and communication graph restrictions.  The distinctions between stability and optimality on graphs are explored. An optimal design method for local feedback controllers is given that decouples the control design from the graph structural properties.  In the case of continuous-time systems, the optimal design method guarantees synchronization on any graph with suitable connectedness properties. In the case of discrete-time systems, a condition for synchronization is that the Mahler measure of unstable eigenvalues of the local systems be restricted by the condition number of the graph. Thus, graphs with better topologies can tolerate a higher degree of inherent instability in the individual node dynamics. A theory of duality between controllers and observers on communication graphs is given, including methods for cooperative output feedback control based on cooperative regulator designs.

In Part 2 of the talk, we discuss graphical games. Standard differential multi-agent game theory has a centralized dynamics affected by the control policies of multiple agent players. We give a new formulation for games on communication graphs. Standard definitions of Nash equilibrium are not useful for graphical games since, though in Nash equilibrium, all agents may not achieve synchronization. A strengthened definition of Interactive Nash equilibrium is given that guarantees that all agents are participants in the same game, and that all agents achieve synchronization while optimizing their own value functions.

Biosketch F.L. Lewis: Member, National Academy of Inventors. Fellow IEEE, Fellow IFAC, Fellow U.K. Institute of  Measurement & Control, Fellow AAAS, 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.  Qian Ren Thousand Talents Consulting Professor, Northeastern University, Shenyang, China. Foreign Expert Scholar, Huazhong University of Science and Technology. IEEE Control Systems Society Distinguished Lecturer.  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.  He is author of 7 U.S. patents, 316 journal papers, 406 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 IEEE Computational Intelligence Society Neural Networks Pioneer Award 2012 and AIAA Intelligent Systems Award 2016.  Distinguished Foreign Scholar at Nanjing Univ. Science & Technology. 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.