{"title":"基于粒子群优化算法的模糊控制规则优化","authors":"Sun Wei, Mingming Liu, Yongbao Song","doi":"10.1109/WGEC.2009.186","DOIUrl":null,"url":null,"abstract":"The selection of fuzzy control rule is one of the keys in fuzzy controller’s design. The article introduces particle swarm optimization (PSO) algorithms optimizing fuzzy control rule in details, and applies the optimized rule to design fuzzy controller. The result of simulation shows that applying PSO to optimize fuzzy control rule is feasible and effective. It enlarges the application scope of PSO algorithms and provides a new way to design fuzzy controller.","PeriodicalId":277950,"journal":{"name":"2009 Third International Conference on Genetic and Evolutionary Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"The Optimizing of Fuzzy Control Rule Based on Particle Swarm Optimization Algorithms\",\"authors\":\"Sun Wei, Mingming Liu, Yongbao Song\",\"doi\":\"10.1109/WGEC.2009.186\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The selection of fuzzy control rule is one of the keys in fuzzy controller’s design. The article introduces particle swarm optimization (PSO) algorithms optimizing fuzzy control rule in details, and applies the optimized rule to design fuzzy controller. The result of simulation shows that applying PSO to optimize fuzzy control rule is feasible and effective. It enlarges the application scope of PSO algorithms and provides a new way to design fuzzy controller.\",\"PeriodicalId\":277950,\"journal\":{\"name\":\"2009 Third International Conference on Genetic and Evolutionary Computing\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Third International Conference on Genetic and Evolutionary Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WGEC.2009.186\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Third International Conference on Genetic and Evolutionary Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WGEC.2009.186","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Optimizing of Fuzzy Control Rule Based on Particle Swarm Optimization Algorithms
The selection of fuzzy control rule is one of the keys in fuzzy controller’s design. The article introduces particle swarm optimization (PSO) algorithms optimizing fuzzy control rule in details, and applies the optimized rule to design fuzzy controller. The result of simulation shows that applying PSO to optimize fuzzy control rule is feasible and effective. It enlarges the application scope of PSO algorithms and provides a new way to design fuzzy controller.
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