{"title":"聚类算法将高斯基函数神经网络补偿器与模糊控制相结合应用于磁轴承系统","authors":"Chao-Ting Chu, H. Chiang, Yung-Sheng Chang","doi":"10.1109/ISNE.2016.7543328","DOIUrl":null,"url":null,"abstract":"This paper proposed clustering algorithms applied Gaussian basis function neural network compensator with fuzzy control for magnetic bearing system (MBS). The nonlinear MBS improved traditional bearing friction losses, and nonlinear system with fuzzy controller and neural network does not require precise MBS mathematical model. We used clustering algorithms which are fuzzy c-means and k-means adjusted Gaussian basis function in neural network. Finally, we used the Lyapunov stability to guarantee MBS convergence, and the experimental results shows proposed algorithm has satisfactory performance in MBS.","PeriodicalId":127324,"journal":{"name":"2016 5th International Symposium on Next-Generation Electronics (ISNE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Clustering algorithms applied Gaussian basis function neural network compensator with fuzzy control for magnetic bearing system\",\"authors\":\"Chao-Ting Chu, H. Chiang, Yung-Sheng Chang\",\"doi\":\"10.1109/ISNE.2016.7543328\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposed clustering algorithms applied Gaussian basis function neural network compensator with fuzzy control for magnetic bearing system (MBS). The nonlinear MBS improved traditional bearing friction losses, and nonlinear system with fuzzy controller and neural network does not require precise MBS mathematical model. We used clustering algorithms which are fuzzy c-means and k-means adjusted Gaussian basis function in neural network. Finally, we used the Lyapunov stability to guarantee MBS convergence, and the experimental results shows proposed algorithm has satisfactory performance in MBS.\",\"PeriodicalId\":127324,\"journal\":{\"name\":\"2016 5th International Symposium on Next-Generation Electronics (ISNE)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 5th International Symposium on Next-Generation Electronics (ISNE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISNE.2016.7543328\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 5th International Symposium on Next-Generation Electronics (ISNE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISNE.2016.7543328","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Clustering algorithms applied Gaussian basis function neural network compensator with fuzzy control for magnetic bearing system
This paper proposed clustering algorithms applied Gaussian basis function neural network compensator with fuzzy control for magnetic bearing system (MBS). The nonlinear MBS improved traditional bearing friction losses, and nonlinear system with fuzzy controller and neural network does not require precise MBS mathematical model. We used clustering algorithms which are fuzzy c-means and k-means adjusted Gaussian basis function in neural network. Finally, we used the Lyapunov stability to guarantee MBS convergence, and the experimental results shows proposed algorithm has satisfactory performance in MBS.