In this book, control and filtering problems for several classes of stochastic networked systems are discussed. In each chapter, the stability, robustness, reliability, consensus performance, and/or disturbance attenuation levels are investigated within a unified theoretical framework. The aim is to derive the sufficient conditions such that the resulting systems achieve the prescribed design requirements despite all the network-induced phenomena. Further, novel notions such as randomly occurring sensor failures and consensus in probability are discussed. Finally, the theories/techniques developed are applied to emerging research areas.
- Unifies existing and emerging concepts concerning stochastic control/filtering and distributed control/filtering with an emphasis on a variety of network-induced complexities
- Includes concepts like randomly occurring sensor failures and consensus in probability (with respect to time-varying stochastic multi-agent systems)
- Exploits the recursive linear matrix inequality approach, completing the square method, Hamilton-Jacobi inequality approach, and parameter-dependent matrix inequality approach to handle the emerging mathematical/computational challenges
- Captures recent advances of theories, techniques, and applications of stochastic control as well as filtering from an engineering-oriented perspective
- Gives simulation examples in each chapter to reflect the engineering practice
|Sold by:||Barnes & Noble|
|File size:||15 MB|
|Note:||This product may take a few minutes to download.|
About the Author
Lifeng Ma was born in Jiangsu, China, in 1982. He received the B.Sc. degree in automation from Jiangsu University, Zhenjiang, China, in 2004, and the Ph.D. degree in control science and engineering from the Nanjing University of Science and Technology, Nanjing, China, in 2010.
From 2008 to 2009, he was a visiting Ph.D. student with the Department of Information Systems and Computing, Brunel University London, Uxbridge, U.K. He was a Research Associate with the Department of Mechanical Engineering, University of Hong Kong, Hong Kong, in 2010, for four months, and 2011, for five months. From 2015 to 2017, he was a Visiting Research Fellow with King’s College London, London, U.K. He is currently a Professor with the School of Automation, Nanjing University of Science and Technology, Nanjing, China.
Prof. Ma has published over 20 papers in refereed international journals. His current research interests include nonlinear control and signal processing, variable structure control, distributed control and filtering, time-varying systems, and multi-agent systems.
Prof. Ma serves as an Editor for Neurocomputing. He is a very 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 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. 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.
Professor Wang serves (or has served) as the Editor-in-Chief for Neurocomputing 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.
Yuming Bo was born in Jiangsu, China, in 1965. He received both the B.Sc. degree and the M.Sc. degree in Automatic Control in 1984 and 1987 from Nanjing University of Science and Technology, Nanjing, China, and the Ph.D. degree in Control Science and Control Engineering in 2005 from Nanjing University of Science and Technology, Nanjing, China.
He is currently a professor with the School of Automation, Nanjing University of Science and Technology, Nanjing, China. He was a teaching assistant in the Department of Automation, Nanjing University of Science and Technology, Nanjing, China from 1987, and was then promoted to a Lecturer in 1990, Associate Professor in 1996 and to a Professor in 2002. He was a visiting scholar in the Department of Information Systems and Computing, Brunel University London, UK. From April 2009 to March 2010.
Prof. Bo’s research interests include stochastic control and filtering, distributed control systems, as well as video processing. He has published around 30 papers in refereed international journals.
Table of Contents
1.1 Nonlinear Stochastic Networked Systems
1.2 Sliding Model Control
1.3 Distributed Filtering
1.4 Cyber Attacks
1.5 Network-Induced Randomly Occurring Phenomena
1.6 Nonlinear Stochastic Multi-Agent Systems
1.7 Consensus of Nonlinear Multi-Agent Systems with Stochastic Dynamics
1.8 Consensus with Stochastic Topologies
2 Robust H1 Sliding Mode Control for Nonlinear Stochastic Systems with Multiple Data Packet Losses
2.1 Problem Formulation
2.2 Design of Sliding Model Controllers
2.3 An Illustrative Example
3 Sliding Mode Control for a Class of Nonlinear Discrete-Time Networked Systems with Multiple Stochastic Communication Delays
3.1 Problem Formulation
3.2 Design of SMC
3.3 Sliding Mode Controller
3.4 An Illustrative Example
4 Sliding Mode Control for Nonlinear Networked Systems with Stochastic Communication Delays
4.1 Problem Formulation
4.2 Design of SMC
4.3 Sliding Mode Controller
4.4 An Illustrative Example
5 Reliable H1 Control for A Class of Nonlinear Time-Varying Stochastic Systems with Randomly Occurring Sensor Failures
5.1 Problem Formulation
5.2 H1 Performance
5.3 Controller Design
5.4 Numerical Example
6 Event-Triggered Mean Square Consensus Control for Time-Varying Stochastic Multi-Agent System with Sensor Saturations
6.1 Problem Formulation
6.2 Main Results
6.3 Illustrative Example
7 Mean-Square H1 Consensus Control for A Class of Nonlinear Time-Varying Stochastic Multi-Agent Systems: The Finite-Horizon Case
7.1 Problem Formulation
7.2 Main Results
7.3 Illustrative Example
8 Consensus Control for Nonlinear Multi-Agent Systems Subject to Deception Attacks
8.1 Problem Formulation
8.2 Main Results
9 Distributed Event-Based Set-Membership Filtering for A Class of Nonlinear Systems with Sensor Saturations over Sensor Networks
9.1 Problem Formulation
9.2 Distributed Event-Based Set-Membership Filter Design
9.3 An Illustrative Example
10 Variance-Constrained Distributed Filtering for Time varying Systems with Multiplicative Noises and Deception
Attacks over Sensor Networks
10.1 Problem Formulation
10.2 Distributed Filter Design
10.3 Numerical Example
11 Conclusions and Future Topics