Neural-Network-Based Online HJB Solution for Optimal Robust Guaranteed Cost Control of Continuous-Time Uncertain Nonlinear Systems

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 > 先进控制与自动化团队

	Neural-Network-Based Online HJB Solution for Optimal Robust Guaranteed Cost Control of Continuous-Time Uncertain Nonlinear Systems
	Liu, Derong; Wang, Ding; Wang, Fei-Yue; Li, Hongliang; Yang, Xiong
刊名	IEEE TRANSACTIONS ON CYBERNETICS
	2014-12-01
卷号	44 期号:12 页码:2834-2847
关键词	Adaptive critic designs adaptive/approximate dynamic programming (ADP) Hamilton-Jacobi-Bellman (HJB) equation neural networks optimal robust guaranteed cost control uncertain nonlinear systems
英文摘要	In this paper, the infinite horizon optimal robust guaranteed cost control of continuous-time uncertain nonlinear systems is investigated using neural-network-based online solution of Hamilton-Jacobi-Bellman (HJB) equation. By establishing an appropriate bounded function and defining a modified cost function, the optimal robust guaranteed cost control problem is transformed into an optimal control problem. It can be observed that the optimal cost function of the nominal system is nothing but the optimal guaranteed cost of the original uncertain system. A critic neural network is constructed to facilitate the solution of the modified HJB equation corresponding to the nominal system. More importantly, an additional stabilizing term is introduced for helping to verify the stability, which reinforces the updating process of the weight vector and reduces the requirement of an initial stabilizing control. The uniform ultimate boundedness of the closed-loop system is analyzed by using the Lyapunov approach as well. Two simulation examples are provided to verify the effectiveness of the present control approach.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
研究领域[WOS]	Computer Science
关键词[WOS]	DYNAMIC-PROGRAMMING ALGORITHM ; ZERO-SUM GAMES ; FEEDBACK-CONTROL ; INPUT CONSTRAINTS ; UNKNOWN DYNAMICS ; TRACKING CONTROL ; LEARNING CONTROL ; POLICY UPDATE ; DESIGN ; REINFORCEMENT
收录类别	SCI
语种	英语
WOS记录号	WOS:000345629000048
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/3626]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
作者单位	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	Liu, Derong,Wang, Ding,Wang, Fei-Yue,et al. Neural-Network-Based Online HJB Solution for Optimal Robust Guaranteed Cost Control of Continuous-Time Uncertain Nonlinear Systems[J]. IEEE TRANSACTIONS ON CYBERNETICS,2014,44(12):2834-2847.
APA	Liu, Derong,Wang, Ding,Wang, Fei-Yue,Li, Hongliang,&Yang, Xiong.(2014).Neural-Network-Based Online HJB Solution for Optimal Robust Guaranteed Cost Control of Continuous-Time Uncertain Nonlinear Systems.IEEE TRANSACTIONS ON CYBERNETICS,44(12),2834-2847.
MLA	Liu, Derong,et al."Neural-Network-Based Online HJB Solution for Optimal Robust Guaranteed Cost Control of Continuous-Time Uncertain Nonlinear Systems".IEEE TRANSACTIONS ON CYBERNETICS 44.12(2014):2834-2847.