{"title":"A New Methodology for Model Based Robust Fuzzy Digital PID Controller Design","authors":"D. S. Pires, G. L. de Oliveira Serra","doi":"10.1109/GCIS.2012.109","DOIUrl":null,"url":null,"abstract":"In this paper, a robust fuzzy digital PID control strategy, via multiobjective genetic algorithm, based on the gain and phase margins specifications, with applications to uncertain dynamic systems with time delay, is proposed. A mathematical formulation based on the gain and phase margins, the fuzzy model and PID digital controller structures and the time delay of the uncertain dinamic system, is deduced. A multiobjective genetic strategy is defined to tune the fuzzy controller parameters so the gain and phase margins of the fuzzy control system are close to the specified ones. Computational results show the efficiency of the proposed methodology through the accuracy in the gain and phase margins of the PID control system compared to the specified ones and tracking of the reference trajectory.","PeriodicalId":337629,"journal":{"name":"2012 Third Global Congress on Intelligent Systems","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Third Global Congress on Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCIS.2012.109","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
In this paper, a robust fuzzy digital PID control strategy, via multiobjective genetic algorithm, based on the gain and phase margins specifications, with applications to uncertain dynamic systems with time delay, is proposed. A mathematical formulation based on the gain and phase margins, the fuzzy model and PID digital controller structures and the time delay of the uncertain dinamic system, is deduced. A multiobjective genetic strategy is defined to tune the fuzzy controller parameters so the gain and phase margins of the fuzzy control system are close to the specified ones. Computational results show the efficiency of the proposed methodology through the accuracy in the gain and phase margins of the PID control system compared to the specified ones and tracking of the reference trajectory.