Approximation-error-ADP-based optimal tracking control for chaotic systems with convergence proof

作     者：宋睿卓 肖文栋 孙长银 魏庆来 

作者机构：School of Automation and Electrical EngineeringUniversity of Science and Technology Beijing The State Key Laboratory of Management and Control for Complex SystemsInstitute of AutomationChinese Academy of Sciences 

出 版 物：《Chinese Physics B》 (中国物理B（英文版）)

年 卷 期：2013年第22卷第9期

页      面：305-311页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 070105[理学-运筹学与控制论] 070201[理学-理论物理] 081101[工学-控制理论与控制工程] 071101[理学-系统理论] 0811[工学-控制科学与工程] 0701[理学-数学] 0702[理学-物理学] 

基　　金：supported by the Open Research Project from SKLMCCS (Grant No. 20120106) the Fundamental Research Funds for the Central Universities of China (Grant No. FRF-TP-13-018A) the Postdoctoral Science Foundation of China (Grant No. 2013M530527) the National Natural Science Foundation of China (Grant Nos. 61304079, 61125306, and 61034002) 

主　　题：chaotic systems approximation error adaptive dynamic programming optimal tracking control 

摘      要：In this paper, an optimal tracking control scheme is proposed for a class of discrete-time chaotic systems using the approximation-error-based adaptive dynamic programming （ADP） algorithm. Via the system transformation, the optimal tracking problem is transformed into an optimal regulation problem, and then the novel optimal tracking control method is proposed. It is shown that for the iterative ADP algorithm with finite approximation error, the iterative performance index functions can converge to a finite neighborhood of the greatest lower bound of all performance index functions under some convergence conditions. Two examples are given to demonstrate the validity of the proposed optimal tracking control scheme for chaotic systems.