中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Off-policy neuro-optimal control for unknown complex-valued nonlinear systems based on policy iteration

文献类型:期刊论文

作者Song, Ruizhuo1; Wei, Qinglai2; Xiao, Wendong1
刊名NEURAL COMPUTING & APPLICATIONS
出版日期2017-06-01
卷号28期号:6页码:1435-1441
关键词Adaptive Dynamic Programming Approximate Dynamic Programming Adaptive Critic Designs Optimal Control
DOI10.1007/s00521-015-2144-0
文献子类Article
英文摘要This paper establishes an optimal control of unknown complex-valued system. Policy iteration is used to obtain the solution of the Hamilton-Jacobi-Bellman equation. Off-policy learning allows the iterative performance index and iterative control to be obtained by completely unknown dynamics. Critic and action networks are used to get the iterative control and iterative performance index, which execute policy evaluation and policy improvement. Asymptotic stability of the closed-loop system and the convergence of the iterative performance index function are proven. By Lyapunov technique, the uniformly ultimately bounded of the weight error is proven. Simulation study demonstrates the effectiveness of the proposed optimal control method.
WOS关键词OPTIMAL TRACKING CONTROL ; CONTINUOUS-TIME SYSTEMS ; MULTIOBJECTIVE OPTIMAL-CONTROL ; ADAPTIVE OPTIMAL-CONTROL ; OPTIMAL-CONTROL SCHEME ; FEEDBACK-CONTROL ; NETWORK ; ALGORITHM ; DYNAMICS ; DESIGN
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000403939000019
资助机构National Natural Science Foundation of China(61304079 ; Fundamental Research Funds for the Central Universities(FRF-TP-15-056A3) ; Open Research Project from SKLMCCS(20150104) ; 61374105)
源URL[http://ir.ia.ac.cn/handle/173211/13640]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_智能化团队
作者单位1.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Song, Ruizhuo,Wei, Qinglai,Xiao, Wendong. Off-policy neuro-optimal control for unknown complex-valued nonlinear systems based on policy iteration[J]. NEURAL COMPUTING & APPLICATIONS,2017,28(6):1435-1441.
APA Song, Ruizhuo,Wei, Qinglai,&Xiao, Wendong.(2017).Off-policy neuro-optimal control for unknown complex-valued nonlinear systems based on policy iteration.NEURAL COMPUTING & APPLICATIONS,28(6),1435-1441.
MLA Song, Ruizhuo,et al."Off-policy neuro-optimal control for unknown complex-valued nonlinear systems based on policy iteration".NEURAL COMPUTING & APPLICATIONS 28.6(2017):1435-1441.

入库方式: OAI收割

来源:自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。