{"title":"Observer-based Fuzzy Control for Nonlinear Networked Control Systems Based on T-S Fuzzy Model","authors":"Fang Yang, H. Fang","doi":"10.1109/ICCMS.2010.457","DOIUrl":null,"url":null,"abstract":"This paper is concerned with the problem of observer-based fuzzy control design for nonlinear networked control systems (NCSs) with random delays. First, a two-layer T-S fuzzy model based on probability is presented for the NCSs. Stochastic and nonlinear features of the NCSs are incorporated in the model. Then, based on this model a new fuzzy Lyapunov-Krasovskii function is constructed to derive a delay-independent condition such that the closed-loop fuzzy system is asymptotically stable. The control and observer matrices can be solved directly by using linear matrix inequality approach. Finally, an example is included to show the efficiency of the proposed method.","PeriodicalId":153175,"journal":{"name":"2010 Second International Conference on Computer Modeling and Simulation","volume":"229 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Computer Modeling and Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCMS.2010.457","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
This paper is concerned with the problem of observer-based fuzzy control design for nonlinear networked control systems (NCSs) with random delays. First, a two-layer T-S fuzzy model based on probability is presented for the NCSs. Stochastic and nonlinear features of the NCSs are incorporated in the model. Then, based on this model a new fuzzy Lyapunov-Krasovskii function is constructed to derive a delay-independent condition such that the closed-loop fuzzy system is asymptotically stable. The control and observer matrices can be solved directly by using linear matrix inequality approach. Finally, an example is included to show the efficiency of the proposed method.