{"title":"用神经模糊算法设计球梁平衡控制系统","authors":"Huan-Wen Tzeng, Sheng-Kai Hung","doi":"10.1109/FUZZY.2009.5277083","DOIUrl":null,"url":null,"abstract":"This paper proposes a success control application using a Neural-Fuzzy System (NFS) algorithm to control the Ball-Beam balance system, through learning, simulation, and implementation. First, the control system requires control measurement input, enabling it to generate fuzzy control rules automatically, and then the neural-fuzzy system undergoes a series of learning processes to achieve the best simulation results. Finally, the prototype of a control system is realized with good performance.","PeriodicalId":117895,"journal":{"name":"2009 IEEE International Conference on Fuzzy Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Design of ball-beam balance control system using neural-fuzzy algorithm\",\"authors\":\"Huan-Wen Tzeng, Sheng-Kai Hung\",\"doi\":\"10.1109/FUZZY.2009.5277083\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a success control application using a Neural-Fuzzy System (NFS) algorithm to control the Ball-Beam balance system, through learning, simulation, and implementation. First, the control system requires control measurement input, enabling it to generate fuzzy control rules automatically, and then the neural-fuzzy system undergoes a series of learning processes to achieve the best simulation results. Finally, the prototype of a control system is realized with good performance.\",\"PeriodicalId\":117895,\"journal\":{\"name\":\"2009 IEEE International Conference on Fuzzy Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Fuzzy Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FUZZY.2009.5277083\",\"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 IEEE International Conference on Fuzzy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZY.2009.5277083","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design of ball-beam balance control system using neural-fuzzy algorithm
This paper proposes a success control application using a Neural-Fuzzy System (NFS) algorithm to control the Ball-Beam balance system, through learning, simulation, and implementation. First, the control system requires control measurement input, enabling it to generate fuzzy control rules automatically, and then the neural-fuzzy system undergoes a series of learning processes to achieve the best simulation results. Finally, the prototype of a control system is realized with good performance.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
