Parallel Control for Optimal Tracking via Adaptive Dynamic Programming

doi:10.1109/JAS.2020.1003426

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 智能化团队

	Parallel Control for Optimal Tracking via Adaptive Dynamic Programming
	Lu, Jingwei 1,2; Wei, Qinglai 1,2; Wang, Fei-Yue 1,3,4
刊名	IEEE-CAA JOURNAL OF AUTOMATICA SINICA
	2020-11-01
卷号	7 期号:6 页码:1662-1674
关键词	Adaptive dynamic programming (ADP) nonlinear optimal control parallel controller parallel control theory parallel system tracking control neural network (NN)
ISSN号	2329-9266
DOI	10.1109/JAS.2020.1003426
通讯作者	Wei, Qinglai(qinglai.wei@ia.ac.cn)
英文摘要	This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear systems. Unlike existing optimal state feedback control, the control input of the optimal parallel control is introduced into the feedback system. However, due to the introduction of control input into the feedback system, the optimal state feedback control methods can not be applied directly. To address this problem, an augmented system and an augmented performance index function are proposed firstly. Thus, the general nonlinear system is transformed into an affine nonlinear system. The difference between the optimal parallel control and the optimal state feedback control is analyzed theoretically. It is proven that the optimal parallel control with the augmented performance index function can be seen as the suboptimal state feedback control with the traditional performance index function. Moreover, an adaptive dynamic programming (ADP) technique is utilized to implement the optimal parallel tracking control using a critic neural network (NN) to approximate the value function online. The stability analysis of the closed-loop system is performed using the Lyapunov theory, and the tracking error and NN weights errors are uniformly ultimately bounded (UUB). Also, the optimal parallel controller guarantees the continuity of the control input under the circumstance that there are finite jump discontinuities in the reference signals. Finally, the effectiveness of the developed optimal parallel control method is verified in two cases.
资助项目	National Key Reseanch and Development Program of China[2018AAA0101502] ; National Key Reseanch and Development Program of China[2018YFB1702300] ; National Natural Science Foundation of China[61722312] ; National Natural Science Foundation of China[61533019] ; National Natural Science Foundation of China[U1811463] ; National Natural Science Foundation of China[61533017] ; Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles
WOS关键词	TIME NONLINEAR-SYSTEMS ; MANAGEMENT ; SCHEME
WOS研究方向	Automation & Control Systems
语种	英语
CSCD记录号	CSCD:6836404
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000583729100009
资助机构	National Key Reseanch and Development Program of China ; National Natural Science Foundation of China ; Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/41728]
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
通讯作者	Wei, Qinglai
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Qingdao Acad Intelligent Ind, Qingdao 266109, Peoples R China 4.Macau Univ Sci & Technol, Inst Syst Engn, Macau 999078, Peoples R China
推荐引用方式 GB/T 7714	Lu, Jingwei,Wei, Qinglai,Wang, Fei-Yue. Parallel Control for Optimal Tracking via Adaptive Dynamic Programming[J]. IEEE-CAA JOURNAL OF AUTOMATICA SINICA,2020,7(6):1662-1674.
APA	Lu, Jingwei,Wei, Qinglai,&Wang, Fei-Yue.(2020).Parallel Control for Optimal Tracking via Adaptive Dynamic Programming.IEEE-CAA JOURNAL OF AUTOMATICA SINICA,7(6),1662-1674.
MLA	Lu, Jingwei,et al."Parallel Control for Optimal Tracking via Adaptive Dynamic Programming".IEEE-CAA JOURNAL OF AUTOMATICA SINICA 7.6(2020):1662-1674.