Stochastic Control and Filtering over Constrained Communication Networks

Stochastic Control and Filtering over Constrained Communication Networks

by Qinyuan Liu, Zidong Wang, Xiao He

Hardcover(1st ed. 2019)

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Product Details

ISBN-13: 9783030001568
Publisher: Springer International Publishing
Publication date: 10/25/2018
Series: Studies in Systems, Decision and Control , #178
Edition description: 1st ed. 2019
Pages: 222
Product dimensions: 6.10(w) x 9.25(h) x (d)

About the Author

Qinyuan Liu received the B.Eng. degree in measurement and control technology and instrumentation from Huazhong University of Science and Technology, Wuhan, China, in 2012, and the Ph.D. degree in control science and engineering from Tsinghua University, Beijing, China, in 2017. He is currently an Assistant Professor in the Department of Computer Science and Technology, Tongji University, Shanghai, China. From Jul. 2015 to Sep. 2016, he was a Researcher Assistant in the Department of Electronic & Computer Engineering, the Hong Kong University of Science and Technology, Hong Kong. From Jan. 2016 to Jan. 2017, he was an international researcher in the Department of Computer Science, Brunel University London, UK. His research interests include networked control systems, multi-agent systems, and distributed filtering. He is an active reviewer for many international journals.

Zidong Wang was born in Jiangsu, China, in 1966. He received the B.Sc. degree in mathematics in 1986 from Suzhou University, Suzhou, China, and the M.Sc. degree in applied mathematics in 1990 and the Ph.D. degree in electrical engineering in 1994, both from Nanjing University of Science and Technology, Nanjing, China. He is currently Professor of Dynamical Systems and Computing in the Department of Information Systems and Computing, Brunel University London, U.K. From 1990 to 2002, he held teaching and research appointments in universities in China, Germany and the UK. Prof. Wang’s research interests include dynamical systems, signal processing, bioinformatics, control theory and applications. He has published more than 400+ papers in refereed international journals with an h-index of 100. He is a holder of the Alexander von Humboldt Research Fellowship of Germany, the JSPS Research Fellowship of Japan, William Mong Visiting Research Fellowship of Hong Kong. Prof. Wang serves (or has served) as the Editor-in-Chief for Neurocomputing (Elsevier), Editor-in-Chief for Systems Science and Control Engineering (Taylor & Francis), Deputy Editor-in-Chief for International Journal of Systems Science (Taylor & Francis), and an Associate Editor for 12 international journals, including IEEE Transactions on Automatic Control, IEEE Transactions on Control Systems Technology, IEEE Transactions on Neural Networks, IEEE Transactions on Signal Processing, and IEEE Transactions on Systems, Man, and Cybernetics - Part C. He is a Fellow of the IEEE, a Fellow of the Royal Statistical Society and a member of program committee for many international conferences.

Xiao He received the B.E. degree in information technology from the Beijing Institute of Technology, Beijing, China, in 2004, and the Ph.D. degree in control science and engineering from Tsinghua University, Beijing, in 2010. Currently, he is a tenure track Associate Professor with the Department of Automation, Tsinghua University. He has authored more than 40 papers in refereed international journals. His research interests include networked filter and control, and networked fault diagnosis and isolation and their application. Dr. He is now a Full Member of Sigma Xi, the Scientific Research Society, a Senior Member of Chinese Association of Automation (CAA).

Table of Contents

Introduction.- Fundamental Limitations of Networked Systems over Fading Channels.- Event-based H∞ Consensus Control of Multi-agent Systems.- Event-Triggered Resilient Filtering with Measurement Quantization.- Event-based Distributed Filtering of Continuous-time Nonlinear Systems.- Event-based Distributed Filtering over Markovian Switching Topologies.- Event-based Recursive Distributed Filtering.- A Resilient Approach to Distributed Recursive Filter Design.- Consensus-based Recursive Distributed Filtering.- On Kalman-Consensus Filtering with Random Link Failures.- Moving-Horizon Estimation with Binary Encoding Schemes.- Conclusion and Further Work.

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