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Finite horizon optimal tracking control of partially unknown linear continuous-time systems using policy iteration
Li, Chao; Liu, Derong; Li, Hongliang
Source PublicationIET CONTROL THEORY AND APPLICATIONS
2015-08-06
Volume9Issue:12Pages:1791-1801
SubtypeArticle
AbstractIn this study, a neural-network-based online learning algorithm is established to solve the finite horizon linear quadratic tracking (FHLQT) problem for partially unknown continuous-time systems. An augmented problem is constructed with an augmented state which consists of the system state and the reference trajectory. The authors obtain a solution for the augmented problem which is equivalent to the standard solution of the FHLQT problem. To solve the augmented problem with partially unknown system dynamics, they develop a time-varying Riccati equation. A critic neural network is used to approximate the value function and an online learning algorithm is established using the policy iteration technique to solve the time-varying Riccati equation. An integral policy iteration method and an online tuning law are used when the algorithm is implemented without the knowledge of the system drift dynamics and the command generator dynamics. A simulation example is given to show the effectiveness of the established algorithm.
KeywordOptimal Tracking Control
WOS HeadingsScience & Technology ; Technology
WOS KeywordADAPTIVE OPTIMAL-CONTROL ; DYNAMIC-PROGRAMMING ALGORITHM ; ZERO-SUM GAMES ; NONLINEAR-SYSTEMS ; DESIGN
Indexed BySCI
Language英语
WOS Research AreaAutomation & Control Systems ; Engineering ; Instruments & Instrumentation
WOS SubjectAutomation & Control Systems ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS IDWOS:000358509800005
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8881
Collection复杂系统管理与控制国家重点实验室_平行控制
AffiliationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Li, Chao,Liu, Derong,Li, Hongliang. Finite horizon optimal tracking control of partially unknown linear continuous-time systems using policy iteration[J]. IET CONTROL THEORY AND APPLICATIONS,2015,9(12):1791-1801.
APA Li, Chao,Liu, Derong,&Li, Hongliang.(2015).Finite horizon optimal tracking control of partially unknown linear continuous-time systems using policy iteration.IET CONTROL THEORY AND APPLICATIONS,9(12),1791-1801.
MLA Li, Chao,et al."Finite horizon optimal tracking control of partially unknown linear continuous-time systems using policy iteration".IET CONTROL THEORY AND APPLICATIONS 9.12(2015):1791-1801.
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