{"title":"A novel method for type-2 fuzzy logic controller design using a modified biogeography-based optimization","authors":"M. Sayed, M. Saad, H. Emara, E. E. Abou El-Zahab","doi":"10.1109/ICIT.2013.6505643","DOIUrl":null,"url":null,"abstract":"In this paper we apply the modified biogeography-based Optimization (MBBO) to design type-2 fuzzy logic controller (T2FLC) to improve the performance of the plant control system. Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematical models of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. A modified version of the BBO is applied to design the T2FLC to get the optimal parameters of the membership functions of the controller. We test the optimal T2FLC obtained by modified biogeography-based Optimization (MBBO) using benchmark plants and is compared with Particle swarm optimization (PSO).","PeriodicalId":192784,"journal":{"name":"2013 IEEE International Conference on Industrial Technology (ICIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Industrial Technology (ICIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2013.6505643","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper we apply the modified biogeography-based Optimization (MBBO) to design type-2 fuzzy logic controller (T2FLC) to improve the performance of the plant control system. Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematical models of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. A modified version of the BBO is applied to design the T2FLC to get the optimal parameters of the membership functions of the controller. We test the optimal T2FLC obtained by modified biogeography-based Optimization (MBBO) using benchmark plants and is compared with Particle swarm optimization (PSO).