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Adaptive Critic Control with Robust Stabilization for Uncertain Nonlinear Systems de Ding Wang

Adaptive Critic Control with Robust Stabilization for Uncertain Nonlinear Systems: Studies in Systems, Decision and Control, cartea 167

Autor Ding Wang, Chaoxu Mu
en Limba Engleză Hardback – 23 aug 2018
This book reports on the latest advances in adaptive critic control with robust stabilization for uncertain nonlinear systems. Covering the core theory, novel methods, and a number of typical industrial applications related to the robust adaptive critic control field, it develops a comprehensive framework of robust adaptive strategies, including theoretical analysis, algorithm design, simulation verification, and experimental results. As such, it is of interest to university researchers, graduate students, and engineers in the fields of automation, computer science, and electrical engineering wishing to learn about the fundamental principles, methods, algorithms, and applications in the field of robust adaptive critic control. In addition, it promotes the development of robust adaptive critic control approaches, and the construction of higher-level intelligent systems.
 
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Specificații

ISBN-13: 9789811312526
ISBN-10: 9811312524
Pagini: 294
Ilustrații: XVII, 307 p. 131 illus., 129 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.64 kg
Ediția:1st ed. 2019
Editura: Springer Nature Singapore
Colecția Springer
Seria Studies in Systems, Decision and Control

Locul publicării:Singapore, Singapore

Cuprins

A Survey of Robust Adaptive Critic Control Design.- Robust Optimal Control of Nonlinear Systems with Matched Uncertainties.- Observer-Based Online Adaptive Regulation for a Class of Uncertain Nonlinear Systems.- Adaptive Tracking Control of Nonlinear Systems Subject to Matched Uncertainties.- Event-Triggered Robust Stabilization Incorporating an Adaptive Critic Mechanism.- An Improved Adaptive Optimal Regulation Framework with Robust Control Synthesis.- Robust Stabilization and Trajectory Tracking of General Uncertain Nonlinear Systems.- Event-Triggered Nonlinear H∞ Control Design via an Improved Critic Learning Strategy.- Intelligent Critic Control with Disturbance Attenuation for a Micro-Grid System.- Sliding Mode Design for Load Frequency Control with Power System Applications.

Recenzii

“The book presents results on learning-based robust adaptive critic control theory, including self-learning robust stabilization, data-driven robust optimal control, adaptive trajectory tracking, adaptive H1 control design. A general analysis for adaptive critic systems in terms of stability, convergence, optimality, and robustness under uncertain environment is covered.” (Alexandra Rodkina, zbMATH 1407.93006, 2019)

Notă biografică

Dr. Ding Wang is an associate professor in The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences. His main research interests cover adaptive and learning control systems, complex systems and intelligent control, neural networks and neural computing.
Dr. Chaoxu Mu is an associate professor in school of electrical and information engineering, Tianjin University. Her research interests focus mainly on non-linear control theory and applications, adaptive dynamic programming and robust control.

Textul de pe ultima copertă

This book reports on the latest advances in adaptive critic control with robust stabilization for uncertain nonlinear systems. Covering the core theory, novel methods, and a number of typical industrial applications related to the robust adaptive critic control field, it develops a comprehensive framework of robust adaptive strategies, including theoretical analysis, algorithm design, simulation verification, and experimental results. As such, it is of interest to university researchers, graduate students, and engineers in the fields of automation, computer science, and electrical engineering wishing to learn about the fundamental principles, methods, algorithms, and applications in the field of robust adaptive critic control. In addition, it promotes the development of robust adaptive critic control approaches, and the construction of higher-level intelligent systems.
 

Caracteristici

Provides a comprehensive and critical review of the latest advances in adaptive critic based robust control design for nonlinear systems Discusses data-based robust stabilization, trajectory tracking, and event-driven disturbance attenuation Includes theoretical analysis, algorithm design, simulation verification, and experimental results Focuses on robust adaptive critic control methods, and the construction of higher-level intelligent systems