Policy iteration optimal tracking control for chaotic systems by using an adaptive dynamic programming approach

被引：0
|
作者：
魏庆来
刘德荣
徐延才
机构：
[1] TheStateKeyLaboratoryofManagementandControlforComplexSystems,InstituteofAutomation,ChineseAcademyofSciences
来源：
Chinese Physics B. | 2015年 / 24卷 / 03期
关键词：
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A policy iteration algorithm of adaptive dynamic programming(ADP) is developed to solve the optimal tracking control for a class of discrete-time chaotic systems. By system transformations, the optimal tracking problem is transformed into an optimal regulation one. The policy iteration algorithm for discrete-time chaotic systems is first described. Then,the convergence and admissibility properties of the developed policy iteration algorithm are presented, which show that the transformed chaotic system can be stabilized under an arbitrary iterative control law and the iterative performance index function simultaneously converges to the optimum. By implementing the policy iteration algorithm via neural networks,the developed optimal tracking control scheme for chaotic systems is verified by a simulation.
引用
收藏
页数：8
相关论文
共 50 条
  • [1] Policy iteration optimal tracking control for chaotic systems by using an adaptive dynamic programming approach
    Wei Qing-Lai
    Liu De-Rong
    Xu Yan-Cai
    [J]. CHINESE PHYSICS B, 2015, 24 (03)
  • [2] Generalized Policy Iteration Adaptive Dynamic Programming Algorithm for Optimal Tracking Control of a Class of Nonlinear Systems
    Lin, Qiao
    Wei, Qinglai
    Liu, Derong
    [J]. PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC), 2016, : 5009 - 5014
  • [3] Adaptive dynamic programming-based optimal tracking control for nonlinear systems using general value iteration
    Lin, Xiaofeng
    Ding, Qiang
    Kong, Weikai
    Song, Chunning
    Huang, Qingbao
    [J]. 2014 IEEE SYMPOSIUM ON ADAPTIVE DYNAMIC PROGRAMMING AND REINFORCEMENT LEARNING (ADPRL), 2014, : 224 - 229
  • [4] Value Iteration, Adaptive Dynamic Programming, and Optimal Control of Nonlinear Systems
    Bian, Tao
    Jiang, Zhong-Ping
    [J]. 2016 IEEE 55TH CONFERENCE ON DECISION AND CONTROL (CDC), 2016, : 3375 - 3380
  • [5] Adaptive optimal control approach to robust tracking of uncertain linear systems based on policy iteration
    Xu, Dengguo
    Wang, Qinglin
    Li, Yuan
    [J]. MEASUREMENT & CONTROL, 2021, 54 (5-6): : 668 - 680
  • [6] A novel optimal tracking control scheme for a class of discrete-time nonlinear systems using generalised policy iteration adaptive dynamic programming algorithm
    Lin, Qiao
    Wei, Qinglai
    Liu, Derong
    [J]. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2017, 48 (03) : 525 - 534
  • [7] Linear Optimal Tracking Control: An Adaptive Dynamic Programming Approach
    Gao, Weinan
    Jiang, Zhong-Ping
    [J]. 2015 AMERICAN CONTROL CONFERENCE (ACC), 2015, : 4929 - 4934
  • [8] Optimal Learning Control for Discrete-Time Nonlinear Systems Using Generalized Policy Iteration Based Adaptive Dynamic Programming
    Wei, Qinglai
    Liu, Derong
    [J]. 2014 11TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2014, : 1781 - 1786
  • [9] Adaptive Optimal Control for a Class of Nonlinear Systems: The Online Policy Iteration Approach
    He, Shuping
    Fang, Haiyang
    Zhang, Maoguang
    Liu, Fei
    Ding, Zhengtao
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 31 (02) : 549 - 558
  • [10] Discrete-Time Optimal Control via Local Policy Iteration Adaptive Dynamic Programming
    Wei, Qinglai
    Liu, Derong
    Lin, Qiao
    Song, Ruizhuo
    [J]. IEEE TRANSACTIONS ON CYBERNETICS, 2017, 47 (10) : 3367 - 3379
12345