A new approach of optimal control for a class of continuous-time chaotic systems by an online ADP algorithm  

作　　者：宋睿卓 肖文栋 魏庆来 

机构地区：[1]School of Automation and Electrical Engineering,University of Science and Technology Beijing [2]The State Key Laboratory of Management and Control for Complex Systems,Institute of Automation,Chinese Academy of Sciences

出　　处：《Chinese Physics B》2014年第5期138-144,共7页中国物理B（英文版）

基　　金：Project supported by the Open Research Project from the 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 and 61374105);the Natural Science Foundation of Beijing,China(Grant No.4132078 and 4143065)

摘　　要：We develop an online adaptive dynamic programming （ADP） based optimal control scheme for continuous-time chaotic systems. The idea is to use the ADP algorithm to obtain the optimal control input that makes the performance index function reach an optimum. The expression of the performance index function for the chaotic system is first presented. The online ADP algorithm is presented to achieve optimal control. In the ADP structure, neural networks are used to construct a critic network and an action network, which can obtain an approximate performance index function and the control input, respectively. It is proven that the critic parameter error dynamics and the closed-loop chaotic systems are uniformly ultimately bounded exponentially. Our simulation results illustrate the performance of the established optimal control method.We develop an online adaptive dynamic programming （ADP） based optimal control scheme for continuous-time chaotic systems. The idea is to use the ADP algorithm to obtain the optimal control input that makes the performance index function reach an optimum. The expression of the performance index function for the chaotic system is first presented. The online ADP algorithm is presented to achieve optimal control. In the ADP structure, neural networks are used to construct a critic network and an action network, which can obtain an approximate performance index function and the control input, respectively. It is proven that the critic parameter error dynamics and the closed-loop chaotic systems are uniformly ultimately bounded exponentially. Our simulation results illustrate the performance of the established optimal control method.

关 键 词：adaptive dynamic programming adaptive critic designs optimal control continuous-time chaoticsystem 

分 类 号：O415.5[理学—理论物理] O232[理学—物理]