Predictive Learning Control for Unknown Nonaffine Nonlinear Systems

This book investigates both theory and various applications of predictive learning control (PLC) which is an advanced technology for complex nonlinear systems. To avoid the difficult modeling problem for complex nonlinear systems, this book begins with the design and theoretical analysis of PLC method without using mechanism model information of the system, and then a series of PLC methods is designed that can cope with system constraints, varying trial lengths, unknown time delay, and available and unavailable system states sequentially. Applications of the PLC on both railway and urban road transportation systems are also studied. The book is intended for researchers, engineers, and graduate students who are interested in predictive control, learning control, intelligent transportation systems and related fields.

The first book focusing on predictive learning control (PLC) for unknown nonaffine nonlinear systems Proposes a series of PLC methods with systematic design for systems under various practical problems Introduces applications of the proposed PLC methods on both railway and urban road transportation systems

Autorentext

Qiongxia Yu received the B.E. and M.E. degrees from Henan Polytechnic University, Jiaozuo, China, in 2009 and 2012, respectively, and the Ph.D. degree from Beijing Jiaotong University, Beijing, China, in 2017. She is currently Lecturer in Henan Polytechnic University. Dr. Yu has published over 20 peer-reviewed journals and conference proceedings. She was awarded the first prize in Natural Science Academic Award of Henan Province in 2021. Her current research interests include learning control, data-driven control, predictive control, and their applications in transportation systems.
Ting Lei received the B.E. degree from Zhengzhou University, Zhengzhou, China, in 2012, and the Ph.D. degree from Beijing Jiaotong University, Beijing, China, in 2020. He is currently Lecturer in Zhengzhou University of Light Industry. Dr. Lei has published 9 peer-reviewed journals and conference proceedings. His current research interests include data-driven control, model free adaptive control, predictive control, and their applications in urban transportation systems.
Fengchen Tian received the B.E. degree in Electrical engineering and automation from Wanjiang University of Technology, Ma'anshan, China, in 2019, where he is currently pursuing the M.E. degree in School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, China. His research interests include data-driven control and learning control.
Zhongsheng Hou received the B.E. and M.E. degrees from Jilin University of Technology, Changchun, China, in 1983 and 1988, respectively, and the Ph.D. degree from Northeastern University, Shenyang, China, in 1994. From 1997 to 2018, he was with Beijing Jiaotong University, Beijing, China, where he was Distinguished Professor and Head of Department of Automatic Control. Currently, he is Chair Professor at Qingdao University, Qingdao, China. Prof. Hou is Founding Director of the Technical Committee on Data Driven Control, Learning and Optimization (DDCLO), Chinese Association of Automation. He is International Federation of Automatic Control Technical Committee Member of both adaptive and learning systems and transportation systems. He is Fellow of both IEEE and Chinese Association of Automation (CAA). Dr. Hou has authored over 400 peer-reviewed journals and conference proceedings and two monographs. His research interests include data-driven control, learning control, and intelligent transportation systems.
Xuhui Bu received the B.E. and M.E. degrees from Henan Polytechnic University, Jiaozuo, China, in 2004 and 2007, respectively, and the Ph.D. degree from Beijing Jiaotong University, Beijing, China, in 2011. He is currently Professor in Henan Polytechnic University. Dr. Bu has authored over 90 peer-reviewed journals and conference proceedings. He was supported by Program for Central Plains Top Young Talents of Henan Province in 2019. His current research interests are mainly related to data-driven control, iterative learning control, traffic control, and networked system control.

Inhalt
Chapter 1: Introduction.- Chapter 2 Predictive Learning Control for Unknown Systems.- Chapter 3 Constrained Predictive Learning Control.- Chapter 4 Predictive Learning Control for Systems with Varying Trial Lengths .- Chapter 5 Predictive Learning Control for Systems with Unknown Time Delay.- Chapter 6 Predictive Learning Control for Systems with Full Available States.- Chapter 7 Predictive Learning Control for Systems with Unavailable States.- Chapter 8 High-Speed Train Automatic Operation Systems.- Chapter 9 Fundamental Two-Region Urban Road Networks.- Chapter 10 Complex Large-Scale Multi-Region Urban Traffic Systems.- Chapter 11 Conclusions.