Overview

This book is inspired by the development of distributed model predictive control of networked systems to save computation and communication sources. The significant new contribution is to show how to design efficient DMPCs that can be coordinated asynchronously with the increasing effectiveness of the event-triggering mechanism and how to improve the event-triggered DMPC for different requirements improvement of control performance, extension to interconnected networked systems, etc. The book is likely to be of interest to the persons who are engaged in researching control theory in academic institutes, the persons who go in for developing control systems in R&D institutes or companies, the control engineers who are engaged in the implementation of control algorithms, and people who are interested in the distributed MPC.

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Reviews

“I would like to recommend this interesting book to students and researchers interested in DMPC.” (Jin Liang, zbMATH 1511.93003, 2023)

Author Information

Yuanyuan Zou is professor of the Department of Automation, Shanghai Jiao Tong University. She received her B.S. degree and M.S. degree from Ludong University in 2002 and 2005, respectively, and her Ph.D. degree from Shanghai Jiao Tong University in 2009. Her research interests include networked distributed control systems and model predictive control, and she has worked in the research area for 10 years. She has published more than 120 papers in journals/conferences and is an associate editor for IET Control Theory & Applications and Asian Journal of Control. Shaoyuan Li is chair professor of the Department of Automation, Shanghai Jiao Tong University and vice director of Key Laboratory of Ministry of Education. Prof. Li received his Ph.D. degree in Computer and System Science from Nankai University in 1997. Five books and more than 300 papers have been published in journals/conferences, which described his research accomplishments. Prof. Li has worked in the area of control theory and engineering for more than 25 years and has worked in the area of distributed model predictive control for more than 13 years.

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