{"title":"A Novel Methodology to obtain Optimal PI Controller Gains using Multi-gene Genetic Programming for FOPTD Systems","authors":"D. Pozo, L. Morales, D. Maldonado, J. Aguilar","doi":"10.1109/ETCM.2018.8580262","DOIUrl":null,"url":null,"abstract":"This paper presents a novel method for tuning a PI controller for a first-order plus time delay (FOPTD) system based on a Multi-gene Genetic Programming (MGGP) and a Particle Swarm Optimization (PSO) algorithm. In our approach, the PSO stablishes a set of optimal gains of the controller for a FOPTD system, based on the plant parameters. Then, the MGGP obtains the mathematical equations to estimate the optimal gains determined by PSO. Finally, to validate the methodology proposed, a group of random systems were selected and tested in MATLAB-SIMULINK, using the calculated equations, focused in its behavior with respect to the maximum overshoot (Mp) and the Integral Square Error (ISE).","PeriodicalId":334574,"journal":{"name":"2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETCM.2018.8580262","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 presents a novel method for tuning a PI controller for a first-order plus time delay (FOPTD) system based on a Multi-gene Genetic Programming (MGGP) and a Particle Swarm Optimization (PSO) algorithm. In our approach, the PSO stablishes a set of optimal gains of the controller for a FOPTD system, based on the plant parameters. Then, the MGGP obtains the mathematical equations to estimate the optimal gains determined by PSO. Finally, to validate the methodology proposed, a group of random systems were selected and tested in MATLAB-SIMULINK, using the calculated equations, focused in its behavior with respect to the maximum overshoot (Mp) and the Integral Square Error (ISE).