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  • 标题:Finsler-based Sampled-data Controller Design for Takagi-Sugeno Systems
  • 本地全文:下载
  • 作者:Adriano N.D. Lopes ; Kevin Guelton ; Laurent Arcese
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:2
  • 页码:7965-7970
  • DOI:10.1016/j.ifacol.2020.12.2199
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper investigates the sampled-data control of continuous-time Takagi-Sugeno (T-S) fuzzy systems. The closed-loop dynamics is rewritten as a T-S system with input time-varying delays. In this context, asynchronous membership functions appears in the closed-loop dynamics. Thus, to reduce the conservatism of design conditions involving mismatch membership functions, a dedicated relaxation scheme is proposed. Then, from a convenient Lyapunov-Krasovskii function and the application of the Finsler’s Lemma, new LMI-based conditions are proposed for the design of sampled-data Parallel-Distributed-Compensation (PDC) controllers. An example is provided to illustrate the effectiveness of the proposed design methodology in simulation, as well as to highlight their conservatism improvement regarding to previous related results from the literature.
  • 关键词:KeywordsSampled-data controllersTakagi-Sugeno modelsLyapunov Krasowskii Functionals
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