ITERATIVE ADAPTIVE DYNAMIC PROGRAM SELF-LEARN OPTIMAL CONTRO

This unique book introduces the iterative adaptive dynamic programming theory from the control systems perspectives, with the most recent results of iterative adaptive dynamic programming methods. Advanced theoretical analysis and some practical applications of iterative adaptive dynamic programming are provided. Furthermore, the practical applications in residential energy systems are also highlighted, showing the good performance of the iterative adaptive dynamic programming methods.

The useful reference text benefits professionals, researchers, academics, graduate and undergraduates students in control engineering.

Contents:

• Principle of Adaptive Dynamic Programming
• Discrete-Time Local Value Iterative Adaptive Dynamic Programming
• Discrete-Time Local Value Iterative Adaptive Dynamic Programming: Admissibility and Terminations Analysis
• Discrete-Time Local Policy Iteration Adaptive Dynamic Programming
• Continuous-Time Time-Varying Policy Iteration
• Adaptive Dynamic Programming for Discrete-Time Zero-Sum Games
• Model-Free Adaptive Optimal Control for Unknown Nonlinear Multi-Player Non-Zero-Sum Game
• Continuous-Time Distributed Policy Iteration for Multi-Controller Nonlinear Systems
• A Novel Data-Based Fault-Tolerant Control Method for Multicontroller Linear Systems Via Distributed Policy Iteration
• A Novel Dual Iterative Q-Learning Method for Optimal Battery Management in Smart Residential Environments
• Mixed Iterative Adaptive Dynamic Programming for Optimal Battery Energy Control in Microgrids
• Error-Tolerant Iterative Adaptive Dynamic Programming for Optimal Renewable Home Energy Scheduling and Battery Management
• Generalized Actor-Critic Learning Optimal Control in Smart Home Energy Management

Readership: Researchers, professionals, academics and undergraduate and graduate students in control engineering.