An Approximate Neuro-Optimal Solution of Discounted Guaranteed Cost Control Design

doi:10.1109/TCYB.2020.2977318

	An Approximate Neuro-Optimal Solution of Discounted Guaranteed Cost Control Design
	Wang, Ding1,2,3 ; Qiao, Junfei 1,2,3; Cheng, Long4,5
发表期刊	IEEE TRANSACTIONS ON CYBERNETICS
ISSN	2168-2267
	2022
卷号	52 期号:1 页码:77-86
通讯作者	Wang, Ding(dingwang@bjut.edu.cn)
摘要	The adaptive optimal feedback stabilization is investigated in this article for discounted guaranteed cost control of uncertain nonlinear dynamical systems. Via theoretical analysis, the guaranteed cost control problem involving a discounted utility is transformed to the design of a discounted optimal control policy for the nominal plant. The size of the neighborhood with respect to uniformly ultimately bounded stability is discussed. Then, for deriving the approximate optimal solution of the modified Hamilton-Jacobi-Bellman equation, an improved self-learning algorithm under the framework of adaptive critic designs is established. It facilitates the neuro-optimal control implementation without an additional requirement of the initial admissible condition. The simulation verification toward several dynamics is provided, involving the F16 aircraft plant, in order to illustrate the effectiveness of the discounted guaranteed cost control method.
关键词	Control design Cost function Optimal control Nonlinear systems Adaptive systems Switches Adaptive learning system discount factor guaranteed cost function neuro-optimal control uncertainty
DOI	10.1109/TCYB.2020.2977318
关键词[WOS]	ROBUST STABILIZATION
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61773373] ; National Natural Science Foundation of China[61873268] ; National Natural Science Foundation of China[U1913209] ; National Natural Science Foundation of China[61890930-5] ; Beijing Natural Science Foundation[JQ19013] ; Beijing Natural Science Foundation[JQ19020] ; National Key Research and Development Project[2018YFC1900800-5]
项目资助者	National Natural Science Foundation of China ; Beijing Natural Science Foundation ; National Key Research and Development Project
WOS研究方向	Automation & Control Systems ; Computer Science
WOS类目	Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS记录号	WOS:000742182700011
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：108[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/47329
专题	复杂系统认知与决策实验室_先进机器人
通讯作者	Wang, Ding
作者单位	1.Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China 2.Beijing Univ Technol, Beijing Key Lab Computat Intelligence & Intellige, Beijing 100124, Peoples R China 3.Beijing Univ Technol, Beijing Artificial Intelligence Inst, Beijing 100124, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Wang, Ding,Qiao, Junfei,Cheng, Long. An Approximate Neuro-Optimal Solution of Discounted Guaranteed Cost Control Design[J]. IEEE TRANSACTIONS ON CYBERNETICS,2022,52(1):77-86.
APA	Wang, Ding,Qiao, Junfei,&Cheng, Long.(2022).An Approximate Neuro-Optimal Solution of Discounted Guaranteed Cost Control Design.IEEE TRANSACTIONS ON CYBERNETICS,52(1),77-86.
MLA	Wang, Ding,et al."An Approximate Neuro-Optimal Solution of Discounted Guaranteed Cost Control Design".IEEE TRANSACTIONS ON CYBERNETICS 52.1(2022):77-86.