{"title":"Comparative Performance Analysis for A MIMO System Based On Various Optimization Techniques","authors":"Piyali Das, R. Mehta, O. P. Roy","doi":"10.1109/ICSENG.2018.8638205","DOIUrl":null,"url":null,"abstract":"This study illustrates the applications of the recently developed modern optimization techniques. Designing a controller for multiple input multiple output is a big challenge in control system application. To overcome the difficulties of analysing MIMO system a comparative statement of various solutions are prepared in this paper. The study is being done on manual tuning of linear quadratic regulator (LQR) parameters over genetic algorithm (GA) and particle swarm optimization (PSO) algorithm based parameters. The best optimized result is shown and discussed in this study. The comparison is being done the basis of standard deviations in the values of parameters and objective functions.","PeriodicalId":356324,"journal":{"name":"2018 26th International Conference on Systems Engineering (ICSEng)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 26th International Conference on Systems Engineering (ICSEng)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSENG.2018.8638205","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This study illustrates the applications of the recently developed modern optimization techniques. Designing a controller for multiple input multiple output is a big challenge in control system application. To overcome the difficulties of analysing MIMO system a comparative statement of various solutions are prepared in this paper. The study is being done on manual tuning of linear quadratic regulator (LQR) parameters over genetic algorithm (GA) and particle swarm optimization (PSO) algorithm based parameters. The best optimized result is shown and discussed in this study. The comparison is being done the basis of standard deviations in the values of parameters and objective functions.