{"title":"Design of adaptive fuzzy controller with observer using modulated membership functions","authors":"L. Yao, J. Jiang","doi":"10.1109/ICMIC.2011.5973759","DOIUrl":null,"url":null,"abstract":"An online tuning observer based adaptive fuzzy controller with modulated membership function (OAFCMMF) for uncertain nonlinear systems is proposed in this paper. By including micro-genetic algorithm (MGA), the width of the membership functions is modulated based on fuzzy orthogonal condition. The proposed fuzzy controller can online adjust not only weighting factors in the consequence part but also the membership functions in the antecedent part. Computation time is shortened to improve controller performance. Moreover, we use fitness function for online tuning the parameter vector of the fuzzy controller. The fitness function is based on stability criterion established by Lyapunov method. For meeting stability condition, a supervisory controller is implemented in a closed-loop nonlinear system to smoothen controller operation.","PeriodicalId":210380,"journal":{"name":"Proceedings of 2011 International Conference on Modelling, Identification and Control","volume":"108 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2011 International Conference on Modelling, Identification and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMIC.2011.5973759","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
An online tuning observer based adaptive fuzzy controller with modulated membership function (OAFCMMF) for uncertain nonlinear systems is proposed in this paper. By including micro-genetic algorithm (MGA), the width of the membership functions is modulated based on fuzzy orthogonal condition. The proposed fuzzy controller can online adjust not only weighting factors in the consequence part but also the membership functions in the antecedent part. Computation time is shortened to improve controller performance. Moreover, we use fitness function for online tuning the parameter vector of the fuzzy controller. The fitness function is based on stability criterion established by Lyapunov method. For meeting stability condition, a supervisory controller is implemented in a closed-loop nonlinear system to smoothen controller operation.