{"title":"基于遗传算法的模糊PID控制研究","authors":"Lou Guo-huan, Wu Hongbin","doi":"10.1109/CCDC.2009.5195298","DOIUrl":null,"url":null,"abstract":"This paper presents an improved fuzzy PID controller in order to improve the control performance for complex systems, in which the normal PID controller is not suitable in such case. By using genetic algorithm to optimize the fuzzy control rules, the proportional, integral and differential gains of the PID controller are tuned online. Experimental results show that this method is effective.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Study of the fuzzy PID control based on genetic algorithm\",\"authors\":\"Lou Guo-huan, Wu Hongbin\",\"doi\":\"10.1109/CCDC.2009.5195298\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an improved fuzzy PID controller in order to improve the control performance for complex systems, in which the normal PID controller is not suitable in such case. By using genetic algorithm to optimize the fuzzy control rules, the proportional, integral and differential gains of the PID controller are tuned online. Experimental results show that this method is effective.\",\"PeriodicalId\":127110,\"journal\":{\"name\":\"2009 Chinese Control and Decision Conference\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Chinese Control and Decision Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCDC.2009.5195298\",\"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 Chinese Control and Decision Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2009.5195298","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study of the fuzzy PID control based on genetic algorithm
This paper presents an improved fuzzy PID controller in order to improve the control performance for complex systems, in which the normal PID controller is not suitable in such case. By using genetic algorithm to optimize the fuzzy control rules, the proportional, integral and differential gains of the PID controller are tuned online. Experimental results show that this method is effective.
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