{"title":"Fuzzy Lyapunov decentralized control of Takagi-Sugeno interconnected descriptors","authors":"D. Jabri, K. Guelton, N. Manamanni, M. Abdelkrim","doi":"10.1109/CICA.2009.4982780","DOIUrl":null,"url":null,"abstract":"This paper deals with decentralized stabilization of nonlinear systems composed of interconnected Takagi-Sugeno fuzzy descriptors. To ensure the stability of the overall closed-loop system, a set of decentralized Parallel Distributed Compensations (PDC) controllers is employed. The stability conditions are then derived into Linear Matrix Inequalities (LMI) using a fuzzy Lyapunov function for less conservatism. Nevertheless, it contains decision parameters that are not available in practice. So the LMIs are casted into relaxed quadratic conditions using simple assumptions. Finally, a numerical example is proposed to illustrate the effectiveness of the suggested decentralized approach.","PeriodicalId":383751,"journal":{"name":"2009 IEEE Symposium on Computational Intelligence in Control and Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Symposium on Computational Intelligence in Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICA.2009.4982780","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
This paper deals with decentralized stabilization of nonlinear systems composed of interconnected Takagi-Sugeno fuzzy descriptors. To ensure the stability of the overall closed-loop system, a set of decentralized Parallel Distributed Compensations (PDC) controllers is employed. The stability conditions are then derived into Linear Matrix Inequalities (LMI) using a fuzzy Lyapunov function for less conservatism. Nevertheless, it contains decision parameters that are not available in practice. So the LMIs are casted into relaxed quadratic conditions using simple assumptions. Finally, a numerical example is proposed to illustrate the effectiveness of the suggested decentralized approach.
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