{"title":"模糊逻辑控制器设计:一个案例研究","authors":"L. Mastacan, I. Olah, L.I. Anita, T. Peiu","doi":"10.1109/INES.1997.632422","DOIUrl":null,"url":null,"abstract":"An approach to designing fuzzy logic controllers based on the knowledge about how to control a process and the experience of operators working with the process is presented. The fuzzy control goals are to reach the best transient and steady state performances. To obtain these performances, the rule base and fuzzy set membership functions of the fuzzy logic controllers must be adjusted. Two approaches are developed. One approach is to use an operator to change the fuzzy controller parameters by trials and errors. Another approach is to design a self organizer fuzzy controller. Some examples of fuzzy temperature control systems are presented.","PeriodicalId":161975,"journal":{"name":"Proceedings of IEEE International Conference on Intelligent Engineering Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Fuzzy logic controllers design: a case study\",\"authors\":\"L. Mastacan, I. Olah, L.I. Anita, T. Peiu\",\"doi\":\"10.1109/INES.1997.632422\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An approach to designing fuzzy logic controllers based on the knowledge about how to control a process and the experience of operators working with the process is presented. The fuzzy control goals are to reach the best transient and steady state performances. To obtain these performances, the rule base and fuzzy set membership functions of the fuzzy logic controllers must be adjusted. Two approaches are developed. One approach is to use an operator to change the fuzzy controller parameters by trials and errors. Another approach is to design a self organizer fuzzy controller. Some examples of fuzzy temperature control systems are presented.\",\"PeriodicalId\":161975,\"journal\":{\"name\":\"Proceedings of IEEE International Conference on Intelligent Engineering Systems\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of IEEE International Conference on Intelligent Engineering Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INES.1997.632422\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of IEEE International Conference on Intelligent Engineering Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INES.1997.632422","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An approach to designing fuzzy logic controllers based on the knowledge about how to control a process and the experience of operators working with the process is presented. The fuzzy control goals are to reach the best transient and steady state performances. To obtain these performances, the rule base and fuzzy set membership functions of the fuzzy logic controllers must be adjusted. Two approaches are developed. One approach is to use an operator to change the fuzzy controller parameters by trials and errors. Another approach is to design a self organizer fuzzy controller. Some examples of fuzzy temperature control systems are presented.