{"title":"基于遗传算法的非线性系统多目标控制设计","authors":"A. Hajiloo, W. Xie","doi":"10.1109/INISTA.2014.6873593","DOIUrl":null,"url":null,"abstract":"The problem of multi-objective feedback controller design of nonlinear systems is solved in this paper. The T-S fuzzy model is adopted to describe the nonlinear systems and genetic algorithm is used to identify the T-S fuzzy model. The identified T-S fuzzy model is reduced by applying Higher Order Singular Value Decomposition (HOSVD) method. Based on the reduced T-S fuzzy model, an optimal state feedback controller is designed by achieving the trade-off among three conflicting object functions using the optimal Pareto frontier. The simulation results reveal the effectiveness of the proposed method.","PeriodicalId":339652,"journal":{"name":"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Multi-objective control design of the nonlinear systems using genetic algorithm\",\"authors\":\"A. Hajiloo, W. Xie\",\"doi\":\"10.1109/INISTA.2014.6873593\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem of multi-objective feedback controller design of nonlinear systems is solved in this paper. The T-S fuzzy model is adopted to describe the nonlinear systems and genetic algorithm is used to identify the T-S fuzzy model. The identified T-S fuzzy model is reduced by applying Higher Order Singular Value Decomposition (HOSVD) method. Based on the reduced T-S fuzzy model, an optimal state feedback controller is designed by achieving the trade-off among three conflicting object functions using the optimal Pareto frontier. The simulation results reveal the effectiveness of the proposed method.\",\"PeriodicalId\":339652,\"journal\":{\"name\":\"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INISTA.2014.6873593\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INISTA.2014.6873593","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-objective control design of the nonlinear systems using genetic algorithm
The problem of multi-objective feedback controller design of nonlinear systems is solved in this paper. The T-S fuzzy model is adopted to describe the nonlinear systems and genetic algorithm is used to identify the T-S fuzzy model. The identified T-S fuzzy model is reduced by applying Higher Order Singular Value Decomposition (HOSVD) method. Based on the reduced T-S fuzzy model, an optimal state feedback controller is designed by achieving the trade-off among three conflicting object functions using the optimal Pareto frontier. The simulation results reveal the effectiveness of the proposed method.