Intelligent Control of Nonlinear Systems and Nonlinear Multi-Agent Systems with Complex Constraints

Unveiling Cutting-Edge Research and Insights
Erscheinungsjahr 2025
ISBN: 978-981-960319-0
Verlag: Springer Nature Singapore

Buch, Englisch, Band 16, 200 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 532 g

Reihe: Intelligent Control and Learning Systems

This book proposes an integrated design method for intelligent adaptive controllers to overcome the negative effects of various constraints on nonlinear systems and nonlinear multiagent systems in practical applications. The book rigorously provides problem analysis, controller design, and stability theory. In addition, numerous simulation examples are given to demonstrate the validity of the corresponding intelligent control methods, and the simulation results are illustrated in detail with graphs and tables. The methods proposed in this book eliminate some limitations of existing control methods in nonlinear systems and nonlinear multiagent systems with complex constraints and broaden the practical applications of intelligent control methods in industrial automation.

Zielgruppe

Research

Autoren/Hrsg.

Ren, Hongru

Lu, Renquan

Ma, Hui

Zhou, Qi

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik

Inhaltsverzeichnis

Introduction.- Prescribed Performance Control with Actuator Failures.- Approximation-Based Nussbaum Gain Adaptive Control with Periodic Disturbances.- Adaptive Dynamic Event-Triggered Control Using Disturbance Observer.- Adaptive Fuzzy Control with Output Constraint.

Über Autor(innen)

Hongru Ren received the B.E. and Ph.D. degrees in control science and engineering from the University of Science and Technology of China, Hefei, China, in 2013 and 2019, respectively. His research interests include complex nonlinear systems, networked control systems, and unmanned autonomous systems.

Hui Ma received the B.S. degree in mathematics from Harbin Normal University, Harbin, China, in 2016, the M.S. degree in applied mathematics from Bohai University, Jinzhou, China, in 2019, and the Ph.D. degree in control science and engineering from the Guangdong University of Technology, Guangzhou, China, in 2021. From 2022 to 2023, she was Postdoctoral Fellow with the School of Mathematics and Statistics, Guangdong University of Technology, Guangzhou, China. She is currently with the School of Mathematics and Statistics, Guangdong University of Technology. Her research interests include nonlinear systems, adaptive neural network control, and adaptive fuzzy control. She was Recipient of the fellowship of China National Postdoctoral Program for Innovative Talents.

Qi Zhou received the B.S. and MS. degrees in mathematics from Bohai University, Jinzhou, China, in 2006 and 2009, respectively, and the Ph.D. degree in control science and engineering from the University of Science and Technology, Nanjing, China, in 2013. Her research interests include fuzzy-logic control, neural control, and robust control for nonlinear systems.

Renquan Lu received the Ph.D. degree in control science and engineering from Zhejiang University, Hangzhou, China, in 2004. He is currently Professor of control science and engineering with the School of Automation, Guangdong University of Technology, Guangzhou, China. His research was supported by the National Science Foundation for Distinguished Young Scholars of China in 2014, the Yangtze River Scholars Program by the Ministry of Education of China in 2017, the Foundation for Innovative Research Groups of the National Natural Science Foundation of China in 2022. His research interests include complex systems, networked control systems, and nonlinear systems.