Dynamic Event-Triggered Fault Diagnosis, State Estimation, and Predictive Control for Networked Systems
Idioma: inglés
Editorial: Taylor & Francis Ltd (Sales) Mai 2026, 2026
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Neuware - The four novel Dynamic Event-Triggered Mechanisms (DETMs) in this book are for complex networked systems that optimize resource utilization while preserving system performance. These include hybrid dynamic variables-dependent ETMs, hybrid adjusting variables-dependent ETMs, bounded dynamic variable/time-varying threshold-dependent ETMs, and terminal constraint set-dependent mixed time/event-triggered mechanisms. It explores applications across fault diagnosis in networked systems, finite-time state estimation for complex dynamical networks, and MPC implementation. - Presents a systematic study on dynamic event-triggered mechanisms - Reviews comprehensive research results on dynamic event-triggered fault diagnosis, state estimation, and MPC - Explores how these theories can be applied to the practical engineering problem of load frequency control in power systems - Discusses complex factors including cyber-attacks, multiple timescales, jumping system parameters, hard constraints, polytopic uncertainties, nonlinearities, and limited network/computing resources - Includes numerous simulations and examples to validate the theoretical results including single-link rigid robot model systems, motor systems, and power systems. This book is aimed at graduate students and researchers in control systems, computer sciences, and signal processing.…
N° de ref. del artículo 9781041165378
- Título
- Dynamic Event-Triggered Fault Diagnosis, State Estimation, and Predictive Control for Networked Systems
- Autor
- Min Wu
- Editorial
- Taylor & Francis Ltd (Sales) Mai 2026
- Año de publicación
- 2026
- Estado
- Neu
- Encuadernación
- Buch
- Idioma
- inglés
- ISBN 10
- 1041165374
- ISBN 13
- 9781041165378
- Peso del artículo
- 562 gramos
- Dimensiones
- 234x156x18 mm
The four novel Dynamic Event-Triggered Mechanisms (DETMs) in this book are for complex networked systems that optimize resource utilization while preserving system performance. These include hybrid dynamic variables-dependent ETMs, hybrid adjusting variables-dependent ETMs, bounded dynamic variable/time-varying threshold-dependent ETMs, and terminal constraint set-dependent mixed time/event-triggered mechanisms. It explores applications across fault diagnosis in networked systems, finite-time state estimation for complex dynamical networks, and MPC implementation.
- Presents a systematic study on dynamic event-triggered mechanisms
- Reviews comprehensive research results on dynamic event-triggered fault diagnosis, state estimation, and MPC
- Explores how these theories can be applied to the practical engineering problem of load frequency control in power systems
- Discusses complex factors including cyber-attacks, multiple timescales, jumping system parameters, hard constraints, polytopic uncertainties, nonlinearities, and limited network/computing resources
- Includes numerous simulations and examples to validate the theoretical results including single-link rigid robot model systems, motor systems, and power systems.
This book is aimed at graduate students and researchers in control systems, computer sciences, and signal processing.
“Sinopsis” puede pertenecer a otra edición de este título.
Acerca del autor
Xiongbo Wan received the B.S. degree in information and computing science from Huazhong Agricultural University, Wuhan, China, in 2006, and the M.S. degree in probability theory and mathematical statistics and the Ph.D. degree in control theory and engineering from the Huazhong University of Science and Technology, Wuhan, in 2008 and 2011, respectively. From December 2012 to June 2013, he was a Visiting Scholar with Akita Prefectural University, Akita, Japan. From July 2011 to December 2014, he was a Lecturer and then an Associate Professor with the College of Engineering, Huazhong Agricultural University. From December 2016 to November 2017, he was a Visiting Scholar with the Department of Computer Science, Brunel University London, Uxbridge, U.K. Since 2015, he has been with the China University of Geosciences, Wuhan, where he is currently a Professor with the School of Automation. His research interests include fault diagnosis, state estimation and model predictive control of complex networked systems. Prof. Wan is currently a very active reviewer for many international journals.
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 B.Sc. degree in Mathematics in 1986 from Suzhou University, Suzhou, the M.Sc. degree in Applied Mathematics in 1990 and the Ph.D. 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.
Min Wu received the B.S. and M.S. degrees in engineering from Central South University, Changsha, China, in 1983 and 1986, respectively, and the Ph.D. degree in engineering from the Tokyo Institute of Technology, Tokyo, Japan, in 1999. He was a Faculty Member with the School of Information Science and Engineering, Central South University, from 1986 to 2014, and was promoted to a Professor in 1994. In 2014, he joined the China University of Geosciences, Wuhan, China, where he is a Professor with the School of Automation. He was a Visiting Scholar with the Department of Electrical Engineering, Tohoku University, Sendai, Japan, from 1989 to 1990, and a Visiting Research Scholar with the Department of Control and Systems Engineering, Tokyo Institute of Technology, from 1996 to 1999. He was a Visiting Professor with the School of Mechanical, Materials, Manufacturing Engineering and Management, University of Nottingham, Nottingham, U.K., from 2001 to 2002. His current research interests include robust control, process control, and intelligent systems. Professor Wu is a Fellow of the IEEE, a Fellow of the Chinese Association of Automation (CAA Fellow), a recipient of the IFAC Control Engineering Practice Prize Paper Award, in 1999 (together with M. Nakano and J. She), and a very active reviewer for many international journals.
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