{"title":"基于量子进化算法的2型模糊PD控制器整定","authors":"S. Cho, Joon-Woo Lee, Jujang Lee","doi":"10.1109/DEST.2011.5936641","DOIUrl":null,"url":null,"abstract":"Fuzzy Logic Controller (FLC) is used widely since it can control non-linear system which are hard to be solved by conventional control method. The design of fuzzy logic controller (FLC), however, has some difficulties such as formation of the fuzzy rules, tuning of the scale factor and the rule explosion. The decision of fuzzy rules are not easy since the fuzzy rule is formed by the expert's experience. Finding suitable scale factor is difficult as conventional PID ones since it takes long time. As input increase, fuzzy rule increase exponentially. To overcome these problems, the information integration is used for preventing the rule explosion and fixed the fuzzy rules and scaling factor is used. we proposed Fuzzy PD Controller Tuning method by using Quantum-inspired Evolution algorithm (QEA). This proposed method also was demonstrated by control of double inverted pendulum.","PeriodicalId":297420,"journal":{"name":"5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Type-2 Fuzzy PD Controller Tuning using Quantum-inspired Evolutionary algorithm\",\"authors\":\"S. Cho, Joon-Woo Lee, Jujang Lee\",\"doi\":\"10.1109/DEST.2011.5936641\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fuzzy Logic Controller (FLC) is used widely since it can control non-linear system which are hard to be solved by conventional control method. The design of fuzzy logic controller (FLC), however, has some difficulties such as formation of the fuzzy rules, tuning of the scale factor and the rule explosion. The decision of fuzzy rules are not easy since the fuzzy rule is formed by the expert's experience. Finding suitable scale factor is difficult as conventional PID ones since it takes long time. As input increase, fuzzy rule increase exponentially. To overcome these problems, the information integration is used for preventing the rule explosion and fixed the fuzzy rules and scaling factor is used. we proposed Fuzzy PD Controller Tuning method by using Quantum-inspired Evolution algorithm (QEA). This proposed method also was demonstrated by control of double inverted pendulum.\",\"PeriodicalId\":297420,\"journal\":{\"name\":\"5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DEST.2011.5936641\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEST.2011.5936641","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Type-2 Fuzzy PD Controller Tuning using Quantum-inspired Evolutionary algorithm
Fuzzy Logic Controller (FLC) is used widely since it can control non-linear system which are hard to be solved by conventional control method. The design of fuzzy logic controller (FLC), however, has some difficulties such as formation of the fuzzy rules, tuning of the scale factor and the rule explosion. The decision of fuzzy rules are not easy since the fuzzy rule is formed by the expert's experience. Finding suitable scale factor is difficult as conventional PID ones since it takes long time. As input increase, fuzzy rule increase exponentially. To overcome these problems, the information integration is used for preventing the rule explosion and fixed the fuzzy rules and scaling factor is used. we proposed Fuzzy PD Controller Tuning method by using Quantum-inspired Evolution algorithm (QEA). This proposed method also was demonstrated by control of double inverted pendulum.
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