Performance Analysis and Synthesis for Discrete-Time Stochastic Systems with Network-Enhanced Complexities

The book addresses the system performance with a focus on the network-enhanced complexities and developing the engineering-oriented design framework of controllers and filters with potential applications in system sciences, control engineering and signal processing areas. Therefore, it provides a unified treatment on the analysis and synthesis for discrete-time stochastic systems with guarantee of certain performances against network-enhanced complexities with applications in sensor networks and mobile robotics. Such a result will be of great importance in the development of novel control and filtering theories including industrial impact. Key Features Provides original methodologies and emerging concepts to deal with latest issues in the control and filtering with an emphasis on a variety of network-enhanced complexities Gives results of stochastic control and filtering distributed control and filtering, and security control of complex networked systems Captures the essence of performance analysis and synthesis for stochastic control and filtering Concepts and performance indexes proposed reflect the requirements of engineering practice Methodologies developed in this book include backward recursive Riccati difference equation approach and the discrete-time version of input-to-state stability in probability

1 Introduction 1.1 Discrete-Time Stochastic Systems 1.2 Network-Enhanced Complexities1.3 Performance Analysis and Engineering Design Synthesis 1.4 Outline 2 Finite-Horizon H8 Control with Randomly Occurring Non-linearities and Fading Measurements 2.1 Modeling and Problem Formulation 2.2 H8 Performance Analysis2.3 H8 Controller Design 2.4 Simulation Examples 2.5 Summary 3 Finite-Horizon H8 Consensus Control for Multi-Agent Systems with Missing Measurements3.1 Modeling and Problem Formulation3.2 Consensus Performance Analysis 3.3 H8 Controller Design3.4 Simulation Examples3.5 Summary 4 Finite-Horizon Distributed H8 State Estimation with Stochastic Parameters through Sensor Networks4.1 Modeling and Problem Formulation 4.2 H8 Performance Analysis 4.3 Distributed Filter Design4.4 Simulation Examples4.5 Summary 5 Finite-Horizon Dissipative Control for State-Saturated Discrete Time-Varying Systems with Missing Measurements 5.1 Modeling and Problem Formulation5.2 Dissipative Control for Full State Saturation Case 5.3 Dissipative Control for Partial State Saturation Case 5.4 Simulation Examples 5.5 Summary 6 Finite-Horizon H8 Filtering for State-Saturated Discrete Time-Varying Systems with Packet Dropouts6.1 Modeling and Problem Formulation6.2 H8 Filtering for Full State Saturation Case6.3 H8 Filtering for Partial State Saturation Case 6.4 Simulation Examples 6.5 Summary 7 Finite-Horizon Envelope-Constrained H8 Filtering with Fading Measurements 7.1 Modeling and Problem Formulation 7.2 H8 Performance Analysis7.3 Envelope Constraint Analysis7.4 Envelope-Constrained H8 Filter Design 7.5 Simulation Examples 7.6 Summary 8 Distributed Filtering under Uniform Quantizations and Deception Attacks through Sensor Networks8.1 Modeling and Problem Formulation 8.2 Distributed Filter Design 8.3 Boundedness Analysis 8.4 Simulation Examples8.5 Summary 9 Event-Triggered Distributed H8 State Estimation with Packet Dropouts through Sensor Networks 9.1 Modeling and Problem Formulation 9.2 H8 Performance Analysis9.3 H8 Estimator Design 9.4 Simulation Examples9.5 Summary 10 Event-Triggered Consensus Control for Multi-Agent Systems in the Framework of Input-to-State Stability in Probability 10.1 Modeling and Problem Formulation10.2 Analysis of Input-to-State Stability in Probability10.3 Event-triggered Consensus Control for Multi-agent Systems 10.4 Simulation Examples10.5 Summary 11 Event-Triggered Security Control for Discrete-Time Stochastic Systems subject to Cyber-Attacks11.1 Problem Formulation 11.2 Security Performance Analysis 11.3 Security Controller Design 11.4 Simulation Examples 11.5 Summary 12 Event-Triggered Consensus Control for Multi-Agent Systems subject to Cyber-Attacks in the Framework of Observers 12.1 Modeling and Problem Formulation12.2 Consensus Analysis 12.3 Consensus Controller Design 12.4 Simulation Examples 12.5 Summary Bibliography

Derui Ding received both the B.Sc. degree in Industry Engineering in 2004 and the M.Sc. degree in Detection Technology and Automation Equipment in 2007 from Anhui Polytechnic University, Wuhu, China, and the Ph.D. degree in Control Theory and Control Engineering in 2014 from Donghua University, Shanghai, China. Dr. Ding is currently an associate professor with the Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China. He is also a senior research fellow with the School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne, VIC, Australian. From July 2007 to December 2014, he was a teaching assistant and then a lecturer in the Department of Mathematics, Anhui Polytechnic University, Wuhu, China. In January 2015, he, as an associate professor, joined University of Shanghai for Science and Technology, China. From June 2012 to September 2012, he was a research assistant in the Department of Mechanical Engineering, the University of Hong Kong, Hong Kong. From March 2013 to March 2014, he was a visiting scholar in the Department of Information Systems and Computing, Brunel University London, UK. From June 2015 to August 2015, he was a research assistant in the Department of Mathematics, City University of Hong Kong, Hong Kong. His research interests include nonlinear stochastic control and filtering, consensus control of multi-agent systems, as well as distributed filtering of sensor networks. He has published around 50 papers in refereed international journals. He is serving as an Associate Editor for Neurocomputing and has served as a Gest Editor for International Journal of General Systems and Discrete Dynamics in Nature and Society.Zidong Wang is currently Professor of Dynamical Systems and Computing at Brunel University London in the United Kingdom. From January 1997 to December 1998, he was an Alexander von Humboldt research fellow with the Control Engineering Laboratory, Ruhr-University Bochum, Germany. From January 1999 to February 2001, he was a Lecturer with the Department of Mathematics, University of Kaiserslautern, Germany. From March 2001 to July 2002, he was a University Senior Research Fellow with the School of Mathematical and Information Sciences, Coventry University, U.K. In August 2002, he joined the Department of Information Systems and Computing, Brunel University, U.K., as a Lecturer, and was then promoted to a Reader in September 2003 and to a Chair Professor in July 2007. Professor Wang's research interests include dynamical systems, signal processing, bioinformatics, control theory and applications. He has published more than 300 papers in refereed international journals. According to the Web of Science, his publications have received more than 19,636 citations (excluding self-citations) with h-index 87. He was awarded the Humboldt research fellowship in 1996 from Alexander von Humboldt Foundation, the JSPS Research Fellowship in 1998 from Japan Society for the Promotion of Science, and the William Mong Visiting Research Fellowship in 2002 from the University of Hong Kong. Professor Wang is an IEEE Fellow for his contributions to networked control and complex networks. He has served or is serving as an Associate Editor for IEEE Transactions on Automatic Control, IEEE Transactions on Neural Networks, IEEE Transactions on Signal Processing, IEEE Transactions on Systems, Man, and Cybernetics - Part C, IEEE Transactions on Control Systems Technology, Circuits, Systems & Signal Processing, Asian Journal of Control, an Action Editor for Neural Networks, an Editorial Board Member for IET Control Theory and Applications, International Journal of Systems Science, Neurocomputing, International Journal of Computer Mathematics, International Journal of General Systems, and an Associate Editor on the Conference Editorial Board for the IEEE Control Systems Society. He is a Senior Member of the IEEE, a Fellow of the Royal Statistical Society, a member of program committee for many international conferences, and a very active reviewer for many international journals. He was nominated an appreciated reviewer for IEEE Transactions on Signal Processing in 2006-2008 and 2011, an appreciated reviewer for IEEE Transactions on Intelligent Transportation Systems in 2008; an outstanding reviewer for IEEE Transactions on Automatic Control in 2004 and for the journal Automatica in 2000. Guoliang Wei received the B.Sc. degree in mathematics from Henan Normal University, Xinxiang, China, in 1997 and the M.Sc. degree in applied mathematics and the Ph.D. degree in control engineering, both from Donghua University, Shanghai, China, in 2005 and 2008, respectively. He is currently a Professor with the Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China. From March 2010 to May 2011, he was an Alexander von Humboldt Research Fellow in the Institute for Automatic Contr