{"title":"T-S Fuzzy Model-Based Robust Output-Feedback Control for Fractional-Order Systems","authors":"R. Chaibi, M. Yagoubi, B. E. Haiek","doi":"10.23919/ecc54610.2021.9655089","DOIUrl":null,"url":null,"abstract":"This paper proposes a robust dynamic output feedback control for uncertain fractional-order systems based on an uncertain Takagi-Sugeno fuzzy model with a fractional-order satisfying 0<α<1. By means of a specific Lyapunov function, some sufficient conditions, expressed as linear matrix inequalities, are derived to allow the design of a stabilizing dynamic output feedback controller for the said fractional-order system. When compared with previous work, the proposed method not only shows abilities to handle the fuzzy system with the time-derivatives of the membership functions but also can deal with the parametric uncertainties effectively. A simulation example is given to demonstrate the validity of the proposed conditions.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 European Control Conference (ECC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ecc54610.2021.9655089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes a robust dynamic output feedback control for uncertain fractional-order systems based on an uncertain Takagi-Sugeno fuzzy model with a fractional-order satisfying 0<α<1. By means of a specific Lyapunov function, some sufficient conditions, expressed as linear matrix inequalities, are derived to allow the design of a stabilizing dynamic output feedback controller for the said fractional-order system. When compared with previous work, the proposed method not only shows abilities to handle the fuzzy system with the time-derivatives of the membership functions but also can deal with the parametric uncertainties effectively. A simulation example is given to demonstrate the validity of the proposed conditions.