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A data-driven methodology for solving the control strategy of descriptor systems
Zhang DQ(张大庆); Li, Mengmeng; Li JN(李金娜)
Department工业控制网络与系统研究室
Conference Name2013 9th Asian Control Conference, ASCC 2013
Conference DateJune 23-26, 2013
Conference PlaceIstanbul, Turkey
Source Publication2013 9th Asian Control Conference, ASCC 2013
PublisherIEEE Computer Society
Publication PlaceWashington, United States
2013
Pages1-6
Indexed ByEI ; CPCI(ISTP)
EI Accession number20134416932306
WOS IDWOS:000333734900174
Contribution Rank2
ISBN978-1-4673-5769-2
KeywordAlgorithms Computer Simulation Optimal Control Systems Reinforcement Learning
AbstractThis paper is concerned with the reinforcement learning methods for the discrete time descriptor systems. An algorithm, as well as its theoretical basis, is presented. The algorithm can generate the optimal controller for the target descriptor system only by the measured input and output data, with no need of the information about the system state and system matrices. The algorithm can work well not only when the system index is equal or less than one, but also can work well when the index is greater than one. Simulation indicates that the presented method can solve the optimal control problem well for descriptor systems when the system model is not exactly known, but the input and output data can be measured. © 2013 IEEE.
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/13862
Collection工业控制网络与系统研究室
Recommended Citation
GB/T 7714
Zhang DQ,Li, Mengmeng,Li JN. A data-driven methodology for solving the control strategy of descriptor systems[C]. Washington, United States:IEEE Computer Society,2013:1-6.
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