This book investigates the performance limitation issues in networked feedback systems. The fact that networked feedback systems consist of control and communication devices and systems calls for the integration of control theory and information theory. The primary contributions of this book lie in two aspects: the newly-proposed information-theoretic measures and the newly-discovered control performance limitations. We first propose a number of information notions to facilitate the analysis. Using those notions, classes of performance limitations of networked feedback systems, as well as…mehr
This book investigates the performance limitation issues in networked feedback systems. The fact that networked feedback systems consist of control and communication devices and systems calls for the integration of control theory and information theory. The primary contributions of this book lie in two aspects: the newly-proposed information-theoretic measures and the newly-discovered control performance limitations. We first propose a number of information notions to facilitate the analysis. Using those notions, classes of performance limitations of networked feedback systems, as well as state estimation systems, are then investigated. In general, the book presents a unique, cohesive treatment of performance limitation issues of networked feedback systems via an information-theoretic approach. This book is believed to be the first to treat the aforementioned subjects systematically and in a unified manner, offering a unique perspective differing from existing books.
Produktdetails
Produktdetails
Lecture Notes in Control and Information Sciences 465
Song Fang received the B.S. degree in automation from Shandong University, Jinan, China, in 2008, the M.S. degree in control theory and control engineering from Shanghai Jiao Tong University, Shanghai, China, in 2011, and the Ph.D. degree in electronic engineering from City University of Hong Kong, Hong Kong, China, in 2015. He visited the Tokyo Institute of Technology, Yokohama, Japan, as a visiting student researcher from January to April, 2013. His main research interests are in the integration of control theory and information theory, as well as in the inherent limits of the feedback mechanism, control and estimation systems, and signal processing. Jie Chen is a Chair Professor in the Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China. He received the B.S. degree in aerospace engineering from Northwestern Polytechnic University, Xian, China in 1982, the M.S.E. degree in electrical engineering, theM.A. degree in mathematics, and the Ph.D. degree in electrical engineering, all from The University of Michigan, Ann Arbor, Michigan, in 1985, 1987, and 1990, respectively. Prior to joining City University, he was with School of Aerospace Engineering and School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia from 1990 to 1993, and with University of California, Riverside, California from 1994 to 2014, where he was a Professor and served as Professor and Chair for the Department of Electrical Engineering from 2001 to 2006. His main research interests are in the areas of linear multivariable systems theory, system identification, robust control, optimization, time-delay systems, networked control, and multi-agent systems. He is the author of two books, respectively, (with G. Gu) Control-Oriented System Identification: An H-infinity Approach (Wiley-Interscience, 2000), and (with K. Gu and V.L. Kharitonov) Stability of Time-Delay Systems(Birkhauser, 2003). An elected Fellow of IEEE, Fellow of AAAS, Fellow of IFAC and a Yangtze Scholar/Chair Professor of China, Dr. Chen was a recipient of 1996 US National Science Foundation CAREER Award, 2004 SICE International Award, and 2006 Natural Science Foundation of China Outstanding Overseas Young Scholar Award. He served on a number of journal editorial boards, as an Associate Editor and a Guest Editor for the IEEE Transactions on Automatic Control, a Guest Editor for IEEE Control Systems Magazine, an Associate Editor for Automatica, and the founding Editor-in-Chief for Journal of Control Science and Engineering. He is currently an IEEE Control Systems Society (CSS) Distinguished Lecturer and serves as an Associate Editor for SIAM Journal on Control and Optimization. He was a member on IEEE CSS Board of Governors in 2014 and has served as IEEE CSS Chapter Activities Chair since 2015. Hideaki Ishii received the M.Eng. degree in applied systems science from Kyoto University, Kyoto, Japan, in 1998, and the Ph.D. degree in electrical and computer engineering from the University of Toronto, Toronto, ON, Canada, in 2002. He was a Postdoctoral Research Associate with the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign, Urbana, IL, USA, from 2001 to 2004, and a Research Associate with the Department of Information Physics and Computing, The University of Tokyo, Tokyo, Japan, from 2004 to 2007. Currently, he is an Associate Professor in the Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama, Japan. His research interests are in networked control systems, multiagent systems, hybrid systems, cyber security of power systems, and probabilistic algorithms. Dr. Ishii has served as an Associate Editor for the IEEE Transactions on Control of Network Systems and Automatica and previously for the IEEE Transactions on Automatic Control. He is the Chair of the IFAC Technical Committee on Networked Systems. He received the IEEE Control Systems Magazine Outstanding Paper Award in 2015.
Inhaltsangabe
Introduction.- Information Measures and Spectral Analysis.- System Performance Measures.- Channel Blurredness.- Bode-Type Integrals.- MIMO Systems.- Bounds on Power Gain.- State Estimation Systems.- Preliminary Results on Continuous-Time Systems.- Conclusion.
Introduction.- Information Measures and Spectral Analysis.- System Performance Measures.- Channel Blurredness.- Bode-Type Integrals.- MIMO Systems.- Bounds on Power Gain.- State Estimation Systems.- Preliminary Results on Continuous-Time Systems.- Conclusion.
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