Title | Output feedback Q-learning for discrete-time finite-horizon zero-sum games with application to the H-? control |
Author | |
Corresponding Author | Cai, Qianqian |
Publication Years | 2023-04-07
|
DOI | |
Source Title | |
ISSN | 0925-2312
|
EISSN | 1872-8286
|
Volume | 529Pages:48-55 |
Abstract | In this paper, we present a Q-learning framework for solving finite-horizon zero-sum game problems involving the H. control of linear system without knowing the dynamics. Research in the past mainly focused on solving problems in infinite horizon with completely measurable state. However, in the prac-tical engineering, the system state is not always directly accessible, and it is difficult to solve the time-varying Riccati equation associated with the finite-horizon setting directly either. The main contribution of the proposed model-free algorithm is to determine the optimal output feedback policies without mea-surement state in finite-horizon setting. To achieve this goal, we first describe the Q-function caused by finite-horizon problems in the context of state feedback, then we parameterize the Q-functions as input- output vectors functions. Finally, the numerical examples on aircraft dynamics demonstrate the algo-rithm's efficiency. (c) 2023 Published by Elsevier B.V. |
Keywords | |
URL | [Source Record] |
Indexed By | |
Language | English
|
SUSTech Authorship | Others
|
Funding Project | Grants of National Natural Science Foundation of China["U21A20476","U1911401","U22A20221","62273100","62073090"]
; Guang-dong Basic and Applied Basic Research Foundation["2021A1515012554","2020A1515011505"]
|
WOS Research Area | Computer Science
|
WOS Subject | Computer Science, Artificial Intelligence
|
WOS Accession No | WOS:000935337000001
|
Publisher | |
ESI Research Field | COMPUTER SCIENCE
|
Scopus EID | 2-s2.0-85149757845
|
Data Source | Web of Science
|
Citation statistics |
Cited Times [WOS]:0
|
Document Type | Journal Article |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/501408 |
Department | Department of Mechanical and Energy Engineering |
Affiliation | 1.Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Guangdong, Peoples R China 2.Guangdong Univ Technol, Guangdong Prov Key Lab Intelligent Decis & Coopera, Guangzhou 510006, Guangdong, Peoples R China 3.Southern Univ Sci & Technol, Dept Mech & Energy Engn, Shenzhen 518055, Guangdong, Peoples R China |
Recommended Citation GB/T 7714 |
Liu, Mingxiang,Cai, Qianqian,Li, Dandan,et al. Output feedback Q-learning for discrete-time finite-horizon zero-sum games with application to the H-? control[J]. NEUROCOMPUTING,2023,529:48-55.
|
APA |
Liu, Mingxiang,Cai, Qianqian,Li, Dandan,Meng, Wei,&Fu, Minyue.(2023).Output feedback Q-learning for discrete-time finite-horizon zero-sum games with application to the H-? control.NEUROCOMPUTING,529,48-55.
|
MLA |
Liu, Mingxiang,et al."Output feedback Q-learning for discrete-time finite-horizon zero-sum games with application to the H-? control".NEUROCOMPUTING 529(2023):48-55.
|
Files in This Item: | There are no files associated with this item. |
|
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment