Learning and Guaranteed Cost Control With Event-Based Adaptive Critic Implementation
Wang, Ding1,2; Liu, Derong3
Source PublicationIEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
ISSN2162-237X
2018-12-01
Volume29Issue:12Pages:6004-6014
Corresponding AuthorWang, Ding(ding.wang@ia.ac.cn)
AbstractThis paper focuses on the event-triggered guaranteed cost control design of nonlinear systems via a self-learning technique. In brief, an event-based guaranteed cost control strategy of nonlinear systems subjects to matched uncertainties is developed, thereby balancing the performance of guaranteed cost and the actuality of limited communication resource. The original control design is transformed into an optimal control problem with an event-based mechanism, where the relationship of guaranteed cost performance compared to the time-based formulation is discussed. A critic neural network is constructed for implementing the event-based optimal control design with stability guarantee. Simulation experiments are carried out to verify the theoretical results in detail.
KeywordAdaptive dynamic programming event-based design guaranteed cost control optimal control self-learning technique
DOI10.1109/TNNLS.2018.2817256
WOS KeywordINFINITY STATE-FEEDBACK ; SYSTEMS ; STABILIZATION ; STABILITY
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61773373] ; National Natural Science Foundation of China[U1501251] ; National Natural Science Foundation of China[61533017] ; Beijing Natural Science Foundation[4162065] ; Young Elite Scientists Sponsorship Program CAST ; Youth Innovation Promotion Association CAS ; Early Career Development Award of SKLMCCS ; National Natural Science Foundation of China[61773373] ; National Natural Science Foundation of China[U1501251] ; National Natural Science Foundation of China[61533017] ; Beijing Natural Science Foundation[4162065] ; Young Elite Scientists Sponsorship Program CAST ; Youth Innovation Promotion Association CAS ; Early Career Development Award of SKLMCCS
Funding OrganizationNational Natural Science Foundation of China ; Beijing Natural Science Foundation ; Young Elite Scientists Sponsorship Program CAST ; Youth Innovation Promotion Association CAS ; Early Career Development Award of SKLMCCS
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000451230100018
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:42[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/25700
Collection复杂系统管理与控制国家重点实验室_复杂系统智能机理与平行控制团队
Corresponding AuthorWang, Ding
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China
3.Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Guangdong, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Wang, Ding,Liu, Derong. Learning and Guaranteed Cost Control With Event-Based Adaptive Critic Implementation[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2018,29(12):6004-6014.
APA Wang, Ding,&Liu, Derong.(2018).Learning and Guaranteed Cost Control With Event-Based Adaptive Critic Implementation.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,29(12),6004-6014.
MLA Wang, Ding,et al."Learning and Guaranteed Cost Control With Event-Based Adaptive Critic Implementation".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 29.12(2018):6004-6014.
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