{"title":"Fuzzy Remodeling and Synthesys of the Class of Nonlinear Systems Based on the Invariant Ellipsoid Technique","authors":"Yuri V. Talagaev","doi":"10.1109/SUMMA48161.2019.8947501","DOIUrl":null,"url":null,"abstract":"An approach that allows performing the synthesis of a class of nonlinear systems under bounded exogenous disturbances is presented. Its implementation includes two stages. At the first stage the given nonlinear system is replaced by the equivalent Takagi-Sugeno fuzzy model. At the second stage via generalization of the method of invariant ellipsoids we solve the problem of finding fuzzy control that stabilizes the closed-loop system and provides optimal rejection of the effect of exogenous disturbances. The numerical testing results showing the efficiency of the offered method are presented.","PeriodicalId":163496,"journal":{"name":"2019 1st International Conference on Control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 1st International Conference on Control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SUMMA48161.2019.8947501","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
An approach that allows performing the synthesis of a class of nonlinear systems under bounded exogenous disturbances is presented. Its implementation includes two stages. At the first stage the given nonlinear system is replaced by the equivalent Takagi-Sugeno fuzzy model. At the second stage via generalization of the method of invariant ellipsoids we solve the problem of finding fuzzy control that stabilizes the closed-loop system and provides optimal rejection of the effect of exogenous disturbances. The numerical testing results showing the efficiency of the offered method are presented.