Model Predictive Control for Complex Dynamic Systems | Analysis and Synthesis

Model Predictive Control (MPC) has advanced as a robust method for managing complex dynamic systems, surpassing traditional control strategies in performance and constraint handling. This book explores MPC theory and applications, focusing on robust MPC (RMPC) for systems with uncertainties. It examines three system types: networked systems, stochastic switching systems, and nonlinear hybrid systems. It addresses challenges in networked interventions, Markovian jump systems, and nonlinear systems under communication constraints.

• Integrates model predictive control, network-induced constraints, cyber-security issues, and advanced communication protocols
• Covers control and state estimation with a focus on dynamic network systems with complex sampling
• Considers and models network-induced complexities
• Employs several analysis techniques to overcome the recent mathematical/computational difficulties for discrete-time systems
• Deals with practical engineering problems for complex dynamic systems with different kinds of scenario-induced complexities or frame-work-induced complexities

This book is aimed at graduate students and researchers in networks, signal processing, controls, and dynamic complex systems.

Yan Song received the B.Eng. degree in materials science and engineering from Jilin University, Changchun, China, in 2001, the M.Sc. degree in applied mathematics from the University of Electronic Science and Technology of China, Chengdu, China, in 2005, and the Ph.D. degree in control theory and control engineering from Shanghai Jiao Tong University, Shanghai, China, in 2013. From December 2016 to December 2017, she was a Visiting Scholar with the Department of Computer Science, Brunel University London, Uxbridge, U.K.

She is currently a Professor with the Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China. Her research interests include model predictive control, machine learning, and data analysis. She has published over 120 papers in refereed international journals. She is a Distinguished Member of the Chinese Computer Federation (CCF) and a Senior Member of the Chinese Association of Automation (CAA). She is serving as an Associate Editor for International Journal of Systems Science.

Zidong Wang is a Professor of Dynamical Systems and Computing at Brunel University London, West London, United Kingdom. He was born in 1966 in Yangzhou, Jiangsu, China. He received the BSc degree in Mathematics in 1986 from Suzhou University, Suzhou, the MSc degree in Applied Mathematics in 1990 and the PhD degree in Electrical and Computer Engineering in 1994, both from Nanjing University of Science and Technology, Nanjing.

He was appointed as Lecturer in 1990 and Associate Professor in 1994 at Nanjing University of Science and Technology. 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 Computer Science, Brunel University London, 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 600 papers in refereed international journals. 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. He was a recipient of the State Natural Science Award from the State Council of China in 2014 and the Outstanding Science and Technology Development Awards (once in 2005 and twice in 1997) from the National Education Committee of China.

Professor Wang is currently serving or has served as the Editor-in-Chief for International Journal of Systems Science, the Editor-in-Chief for Neurocomputing, Executive Editor for Systems Science and Control Engineering, Subject Editor for Journal of The Franklin Institute, an Associate Editor for IEEE Transactions on Automatic Control, IEEE Transactions on Control Systems Technology, IEEE Transactions on Systems, Man, and Cybernetics - Systems, Asian Journal of Control, Science China Information Sciences, IEEE/CAA Journal of Automatica Sinica, Control Theory and Technology, an Action Editor for Neural Networks, an Editorial Board Member for Information Fusion, IET Control Theory & Applications, Complexity, International Journal of Systems Science, Neurocomputing, International Journal of General Systems, Studies in Autonomic, Data-driven and Industrial Computing, and a member of the Conference Editorial Board for the IEEE Control Systems Society. He served as an Associate Editor for IEEE Transactions on Neural Networks, IEEE Transactions on Systems, Man, and Cybernetics - Part C, IEEE Transactions on Signal Processing, Circuits, Systems & Signal Processing, and an Editorial Board Member for International Journal of Computer Mathematics.

Professor Wang is a Member of the Academia Europaea (section of Physics and Engineering Sciences), a Fellow of the IEEE (for contributions to networked control and complex networks), a Fellow of the Chinese Association of Automation, a Member of the IEEE Press Editorial Board, a Member of the EPSRC Peer Review College of the UK, 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.

Bin Zhang received the B.Sc. degree in mathematics and applied mathematics in 2014 from Yantai University, Yantai, China, the M.Sc. degree in statistics and the Ph.D. degree in control science and control engineering from the University of Shanghai for Science and Technology, Shanghai, China, in 2017 and 2022, respectively.

From Mar. 2022 to Aug. 2024, he was a Post-doctoral Research Fellow with the Department of Automation, Shanghai Jiao Tong University, Shanghai, China. He is currently with the School of Electrical Engineering, Shanghai Dianji University, Shanghai, China. His current research interests include model predictive control, stochastic systems and Cyber-physical systems. Dr. Zhang is currently a reviewer for some international journals, including Automatica, IEEE-TAC, IEEE/CAA Journal of Automatica Sinica, etc.