{"title":"Fuzzy Gain-Scheduling Nonlinear Parametric Uncertain System","authors":"Ebrahim A. Mattar, K. Mutib","doi":"10.1109/CIMSIM.2011.31","DOIUrl":null,"url":null,"abstract":"This paper has presented two main issues related to ∞ H robust fuzzy control. The first has been fuzzy modeling of nonlinear dynamical systems, whereas the second was directed towards ∞ H fuzzy gain-scheduling control systems. Regarding fuzzy modeling, that was achieved by employing TakagiSugeno (T-S) fuzzy modeling technique. Employed (T-S) modeling technique was able to cluster an entire nonlinear global model into linear sub-models. With respect to the ∞ H fuzzy gain-scheduling, the paper first presented an approach for designing ∞ H fuzzy controller for disturbance rejection via defining a suitable Lyapunov potential function of the fuzzy model, hence designing a controller by reducing the problem to a standard Linear Matrix Inequalities (LMI) formulation. ∞ H fuzzy gain-scheduling was achieved via treating the (T-S) fuzzy sub-models as a Linear Parameter Varying (LPV) system, hence synthesizing a scheduling controller for variation in parameters. KeywordsHfuzzy; robust control; Takagi-Sugeno, Time Varying systems","PeriodicalId":125671,"journal":{"name":"2011 Third International Conference on Computational Intelligence, Modelling & Simulation","volume":"48 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Third International Conference on Computational Intelligence, Modelling & Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIMSIM.2011.31","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 has presented two main issues related to ∞ H robust fuzzy control. The first has been fuzzy modeling of nonlinear dynamical systems, whereas the second was directed towards ∞ H fuzzy gain-scheduling control systems. Regarding fuzzy modeling, that was achieved by employing TakagiSugeno (T-S) fuzzy modeling technique. Employed (T-S) modeling technique was able to cluster an entire nonlinear global model into linear sub-models. With respect to the ∞ H fuzzy gain-scheduling, the paper first presented an approach for designing ∞ H fuzzy controller for disturbance rejection via defining a suitable Lyapunov potential function of the fuzzy model, hence designing a controller by reducing the problem to a standard Linear Matrix Inequalities (LMI) formulation. ∞ H fuzzy gain-scheduling was achieved via treating the (T-S) fuzzy sub-models as a Linear Parameter Varying (LPV) system, hence synthesizing a scheduling controller for variation in parameters. KeywordsHfuzzy; robust control; Takagi-Sugeno, Time Varying systems