{"title":"Constrained multivariable predictive controller based on PSO algorithm and T-S fuzzy modeling approach","authors":"T. Ali, Sakly Anis, M. Faouzi","doi":"10.1109/STA.2014.7086785","DOIUrl":null,"url":null,"abstract":"This paper describes the development of a strategy to optimally tune constrained predictive controller of Multi Inputs Multi Outputs Nonlinear system with T-S fuzzy modeling approach. The proposed method consists of using T-S fuzzy modeling to determine process model. The intelligent algorithms Particle Swam Optimization is applied to provide the controls action by solving nonlinear optimization problems which is function of the future prediction outputs and the future inputs. The performance of this strategy is evaluated through its application to Quadruple-Tank Process.","PeriodicalId":125957,"journal":{"name":"2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STA.2014.7086785","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper describes the development of a strategy to optimally tune constrained predictive controller of Multi Inputs Multi Outputs Nonlinear system with T-S fuzzy modeling approach. The proposed method consists of using T-S fuzzy modeling to determine process model. The intelligent algorithms Particle Swam Optimization is applied to provide the controls action by solving nonlinear optimization problems which is function of the future prediction outputs and the future inputs. The performance of this strategy is evaluated through its application to Quadruple-Tank Process.