Adaptive Critic Control with Robust Stabilization for Uncertain Nonlinear Systems [electronic resource] /
Wang, Ding.author.
Mu, Chaoxu.author.
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. .
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.
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. .
Mathematical optimization.
Control and Systems Theory.
Optimization.
Robotics and Automation.