Cooperative Multiagent Control: Stability vs. Optimality
Thursday, February 21, 2013 from 6:30 PM to 8:30 PM (PST)
San Francisco, California
London, United Kingdom
The IEEE Control Systems Society invites to a presentation by an IEEE Distinguished Lecturer.
Cooperative Multiagent Control: Stability vs. Optimality
Prof. Frank L. Lewis
IEEE Fellow, IFAC Fellow
Head, Advanced Controls and Sensors Group, UTA Research Institute
The University of Texas at Arlington, Ft. Worth, Texas
Distributed systems of agents linked by communication networks only have access to information from their neighboring agents, yet must achieve global agreement on team activities to be performed cooperatively. Examples include networked manufacturing systems, wireless sensor networks, networked feedback control systems, and the internet. Sociobiological groups such as flocks, swarms, and herds have built-in mechanisms for cooperative control wherein each individual is influenced only by its nearest neighbors, yet the group achieves consensus behaviors such as heading alignment, leader following, exploration of the environment, and evasion of predators. It was shown by Charles Darwin that local interactions between population groups over long time scales lead to global results such as the evolution of species.
Natural decision systems incorporate notions of optimality, since the resources available to organisms and species are limited. This talk investigates relations between the stability of cooperative control and optimality of cooperative control.
Stability. A method is given for the design of cooperative feedbacks for the continuous-time multi-agent tracker problem (also called pinning control or leader-following) that guarantees stable synchronization on arbitrary graphs with spanning trees. It is seen that this design is a locally optimal control with infinite gain margin. In the case of the discrete-time cooperative tracker, local optimal design yields stability on graphs that satisfy an additional restriction based on the Mahler instability measure of the local agent dynamics.
Optimality. Global optimal control of distributed systems is complicated by the fact that, for general LQR performance indices, the resulting optimal control is not distributed in form. Therefore, it cannot be implemented on a prescribed communication graph topology. A condition is given for the existence of any optimal controllers that be implemented in distributed fashion. This condition shows that for the existence of global optimal controllers of distributed form, the performance index weighting matrices must be selected to depend on the graph structure.
F. L. Lewis, Ph.D., Fellow IEEE, Fellow IFAC, Fellow U.K. Inst. MC,
Professional Engineer Texas, Chartered Engineer U.K.
Moncrief-O'Donnell Endowed Chair
University Distinguished Scholar Professor, University Distinguished Teaching Professor
Senior Fellow, UTA Research Institute
Head, Advanced Controls & Sensors Group
UTA Research Institute
The University of Texas at Arlington
7300 Jack Newell Blvd. S
Ft. Worth, Texas 76118
817-272-5972, fax 272-5989, email@example.com
Biosketch, January 24, 2013
Dr. Lewis was born in Würzburg, Germany, subsequently studying in Chile and Gordonstoun School in Scotland. He obtained the Bachelor's Degree in Physics/Electrical Engineering and the Master's of Electrical Engineering Degree at Rice University in 1971. He spent six years in the U.S. Navy, serving as Navigator aboard the frigate USS Trippe (FF-1075), and Executive Officer and Acting Commanding Officer aboard USS Salinan (ATF-161). In 1977 he received the Master's of Science in Aeronautical Engineering from the University of West Florida. In 1981 he obtained the Ph.D. degree at The Georgia Institute of Technology in Atlanta, where he was employed as a professor from 1981 to 1990. He is a Professor of Electrical Engineering at The University of Texas at Arlington, where he was awarded the Moncrief-O'Donnell Endowed Chair in 1990 at the UTA Research Institute. Fellow of the IEEE, Fellow of IFAC, Fellow of the U.K. Institute of Measurement & Control, Member of the New York Academy of Sciences. Received IEEE Computational Intelligence Society Neural Networks Pioneer Award 2012. Registered Professional Engineer in the State of Texas and Chartered Engineer, U.K. Engineering Council. Charter Member (2004) of the UTA Academy of Distinguished Scholars and Senior Research Fellow of the UTA Research Institute. IEEE Control Systems Society Distinguished Lecturer. Founding Member of the Board of Governors of the Mediterranean Control Association. Has served as Visiting Professor at Democritus University in Greece, Hong Kong University of Science and Technology, Chinese University of Hong Kong, City University of Hong Kong, National University of Singapore, Nanyang Technological University Singapore. Elected Guest Consulting Professor at Shanghai Jiao Tong University and South China University of Technology.
Current interests include intelligent control, distributed control on graphs, neural and fuzzy systems, wireless sensor networks, nonlinear systems, robotics, condition-based maintenance, micro-electro-mechanical systems (MEMS) control, and manufacturing process control. Author of 6 U.S. patents, 250 journal papers, 52 chapters and encyclopedia articles, 360 refereed conference papers, and 15 books including Optimal Control, Optimal Estimation, Applied Optimal Control and Estimation, Aircraft Control and Simulation, Control of Robot Manipulators, Neural Network Control, High-Level Feedback Control with Neural Networks and the IEEE reprint volume Robot Control. Editor of Taylor & Francis Book Series on Automation & Control Engineering. Served/serves on many Editorial Boards including International Journal of Control, Neural Computing and Applications, Optimal Control & Methods, and Int. J. Intelligent Control Systems. Served as Editor for the flagship journal Automatica. Recipient of NSF Research Initiation Grant and continuously funded by NSF since 1982. Since 1991 he has received $7 million in funding from NSF, ARO, AFOSR and other government agencies, including significant DoD SBIR and industry funding. Continuously funded by NSF since 1982. His SBIR program was instrumental in ARRI’s receipt of the US SBA Tibbets Award in 1996. Received Fulbright Research Award 1988, American Society of Engineering Education F.E. Terman Award 1989, Int. Neural Network Soc. Gabor Award 2009, U.K. Inst Measurement & Control Honeywell Field Engineering Medal 2009, three Sigma Xi Research Awards, UTA Halliburton Engineering Research Award, UTA Distinguished Research Award, ARRI Patent Awards, various Best Paper Awards, IEEE Control Systems Society Best Chapter Award (as Founding Chairman of DFW Chapter), and National Sigma Xi Award for Outstanding Chapter (as President of UTA Chapter). Received Outstanding Service Award from the Dallas IEEE Section and selected as Engineer of the year by Ft. Worth IEEE Section. Listed in Ft. Worth Business Press Top 200 Leaders in Manufacturing. Appointed to NAE Committee on Space Station in 1995 and IEEE Control Systems Society Board of Governors in 1996. 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.
When & Where
IEEE Control Systems Society, SCV
The IEEE Control Systems Society is an international scientific, engineering, and professional organization that was founded in 1954 and is dedicated to the advancement of research, development, and practice in automation and control systems. The society and its members are involved in a number of activities, including publishing journals and a magazine, holding a number of conferences, and sponsoring committees in various areas of technical specialization.
The CSS Chapter, Santa Clara Valley, serves the local members and community in Silicon Valley. This includes organizing a regular speaker series in the area of control systems, where experts present their work in R&D and industrial applications.