南方科技大学知识苑(SUSTech KC): Finite-horizon Q-learning for discrete-time zero-sum games with application to H & INFIN;$$ {H}

Title	Finite-horizon Q-learning for discrete-time zero-sum games with application to H & INFIN;$$ {H}_{\infty } $$ control
Author	Liu, Mingxiang 1,2; Cai, Qianqian 1,2,4; Meng, Wei 1,2; Li, Dandan 1,2; Fu, Minyue3
Corresponding Author	Cai, Qianqian
Publication Years	2023
DOI	10.1002/asjc.3027
Source Title	ASIAN JOURNAL OF CONTROL Impact Factor & Quartile
ISSN	1561-8625
EISSN	1934-6093
Abstract	In this paper, we investigate the optimal control strategies for model-free zero-sum games involving the H(infinity )control. The key contribution is the development of a Q-learning algorithm for linear quadratic games without knowing the system dynamics. The finite-horizon setting is more practical than the infinite-horizon setting, but it is difficult to solve the time-varying Riccati equation associated with the finite-horizon setting directly. The proposed algorithm is shown to solve the time-varying Riccati equation iteratively without the use of models, and numerical experiments on aircraft dynamics demonstrate the algorithm's efficiency.
Keywords	finite-horizon H(infinity)control linear quadratic (LQ) control Q-learning zero-sum games
URL	[Source Record]
Indexed By	SCI
Language	English
SUSTech Authorship	Others
Funding Project	National Natural Science Foundation of China["U21A20476","U1911401","62273100"] ; Guangdong Basic and Applied Basic Research Foundation["2020A1515011505","2021A1515012554"]
WOS Research Area	Automation & Control Systems
WOS Subject	Automation & Control Systems
WOS Accession No	WOS:000918012600001
Publisher	WILEY
ESI Research Field	ENGINEERING
Data Source	Web of Science
Citation statistics	Cited Times [WOS]:0
Document Type	Journal Article
Identifier	http://kc.sustech.edu.cn/handle/2SGJ60CL/431001
Department	Department of Mechanical and Energy Engineering
Affiliation	1.Guangdong Univ Technol, Sch Automat, Guangzhou, Peoples R China 2.Guangdong Prov Key Lab Intelligent Decis & Coopera, Guangzhou, Peoples R China 3.Southern Univ Sci & Technol, Dept Mech & Energy Engn, Shenzhen, Peoples R China 4.Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Guangdong, Peoples R China
Recommended Citation GB/T 7714	Liu, Mingxiang,Cai, Qianqian,Meng, Wei,et al. Finite-horizon Q-learning for discrete-time zero-sum games with application to H & INFIN;$$ {H}_{\infty } $$ control[J]. ASIAN JOURNAL OF CONTROL,2023.
APA	Liu, Mingxiang,Cai, Qianqian,Meng, Wei,Li, Dandan,&Fu, Minyue.(2023).Finite-horizon Q-learning for discrete-time zero-sum games with application to H & INFIN;$$ {H}_{\infty } $$ control.ASIAN JOURNAL OF CONTROL.
MLA	Liu, Mingxiang,et al."Finite-horizon Q-learning for discrete-time zero-sum games with application to H & INFIN;$$ {H}_{\infty } $$ control".ASIAN JOURNAL OF CONTROL (2023).

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Finite-horizon Q-learning for discrete-time zero-sum games with application to H & INFIN;$$ {H}_{\infty } $$ control