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报告内容摘要：
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, the global aircraft routing system, 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 is known that groups of fireflies and of crickets align their frequencies, neurons in the brain fall into patterns of interacting burst phenomena, and biological groups fall into the circadian rhythm. 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.
This talk explores the structure of complex distributed naturally occurring and human engineered systems. We review the basic sorts of graphs including random, small world, and scale free. It is shown how these notions can be used to design cooperative control systems for dynamical systems interacting on communication graph topologies. The fundamental ideas behind cooperative control for networked interacting teams are presented, including the graph Laplacian matrix, Fiedler eigenvalue, time to consensus, and consensus values reached. Discussed are local voting protocols, second-order consensus, control of systems in formations, and synchronization of distributed interacting oscillators. Local protocols based only on interactions between neighbors lead to global optimal behavior of distributed teams. Results from graph theory show the importance of the communication structure on the agreement reached by the networked team.

报告人简介：
Frank L. Lewis, Fellow IEEE, Fellow IFAC, Fellow U.K. Institute of Measurement & Control, PE Texas, U.K. Chartered Engineer, is Distinguished Scholar Professor and Moncrief-O’Donnell Chair at University of Texas at Arlington’s Automation & Robotics Research Institute. He obtained the Bachelor's Degree in Physics/EE and the MSEE at Rice University, the MS in Aeronautical Engineering from Univ. W. Florida, and the Ph.D. at The Georgia Institute of Technology in Atlanta. He works in feedback control, intelligent systems, distributed control systems, and sensor networks. He is author of 6 U.S. patents, 216 journal papers, 330 conference papers, 14 books, 44 chapters, and 11 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 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. He served on the NAE Committee on Space Station in 1995. 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. He is an elected Guest Consulting Professor at South China University of Technology and Shanghai Jiao Tong University. Founding Member of the Board of Governors of the Mediterranean Control Association. Helped win the IEEE Control Systems Society Best Chapter Award (as Founding Chairman of DFW Chapter), the National Sigma Xi Award for Outstanding Chapter (as President of UTA Chapter), and the US SBA Tibbets Award in 1996 (as Director of ARRI’s SBIR Program).