Springer Stochastic Control and Filtering over Constrained Communication Networks: 178 (Studies in Systems, Decision and Control, 178)

Stochastic Control and Filtering over Constrained Communication Networks presents up-to-date research developments and novel methodologies on stochastic control and filtering for networked systems under constrained communication networks. It provides a framework of optimal controller/filter design, resilient filter design, stability and performance analysis for the systems considered, subject to various kinds of communication constraints, including signal-to-noise constraints, bandwidth constraints, and packet drops. Several techniques are employed to develop the controllers and filters desired, including: recursive Riccati equations; matrix decomposition; optimal estimation theory; and mathematical optimization methods. Readers will benefit from the book’s new concepts, models and methodologies that have practical significance in control engineering and signal processing.  Stochastic Control and Filtering over Constrained Communication Networks is a practical research reference for engineers dealing with networked control and filtering problems. It is also of interest to academics and students working in control and communication networks. Review “This book is a research monograph, the authors make it be readable for graduate students of control theory. One only need some basic knowledge of stochastic process and control system theory to read it. I believe both beginners and experts can benefit from reading this book.” (Lu Qi, zbMATH 1428.93003, 2020) From the Back Cover Stochastic Control and Filtering over Constrained Communication Networks presents up-to-date research developments and novel methodologies on stochastic control and filtering for networked systems under constrained communication networks. It provides a framework of optimal controller/filter design, resilient filter design, stability and performance analysis for the systems considered, subject to various kinds of communication constraints, including signal-to-noise constraints, bandwidth constraints, and packet drops. Several techniques are employed to develop the controllers and filters desired, including: recursive Riccati equations; matrix decomposition; optimal estimation theory; and mathematical optimization methods. Readers will benefit from the book’s new concepts, models and methodologies that have practical significance in control engineering and signal processing.  Stochastic Control and Filtering over Constrained Communication Networks is a practical research reference for engineers dealing with networked control and filtering problems. It is also of interest to academics and students working in control and communication networks. 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