{"title":"基于RBF神经网络滑模控制器的分数阶Lü系统混沌控制","authors":"Xiaomei Yan, Ding-I Liu","doi":"10.1109/WCICA.2010.5554502","DOIUrl":null,"url":null,"abstract":"A RBF neural network sliding mode controller is presented for chaos control of fractional order Lü system with parametric perturbation and external disturbances, which combines the advantages of RBF neural network and sliding mode control. The controller is given based on the output of RBF neural network and the weights of network can be adjusted online according to the sliding mode reaching law. The stability of the controller is analyzed based on the Lyapunov stability theorem. The simulation results illustrate the effectiveness and robustness of the proposed controller.","PeriodicalId":315420,"journal":{"name":"2010 8th World Congress on Intelligent Control and Automation","volume":"142 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Chaos control of fractional order Lü system via RBF neural network sliding mode controller\",\"authors\":\"Xiaomei Yan, Ding-I Liu\",\"doi\":\"10.1109/WCICA.2010.5554502\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A RBF neural network sliding mode controller is presented for chaos control of fractional order Lü system with parametric perturbation and external disturbances, which combines the advantages of RBF neural network and sliding mode control. The controller is given based on the output of RBF neural network and the weights of network can be adjusted online according to the sliding mode reaching law. The stability of the controller is analyzed based on the Lyapunov stability theorem. The simulation results illustrate the effectiveness and robustness of the proposed controller.\",\"PeriodicalId\":315420,\"journal\":{\"name\":\"2010 8th World Congress on Intelligent Control and Automation\",\"volume\":\"142 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 8th World Congress on Intelligent Control and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCICA.2010.5554502\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 8th World Congress on Intelligent Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCICA.2010.5554502","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Chaos control of fractional order Lü system via RBF neural network sliding mode controller
A RBF neural network sliding mode controller is presented for chaos control of fractional order Lü system with parametric perturbation and external disturbances, which combines the advantages of RBF neural network and sliding mode control. The controller is given based on the output of RBF neural network and the weights of network can be adjusted online according to the sliding mode reaching law. The stability of the controller is analyzed based on the Lyapunov stability theorem. The simulation results illustrate the effectiveness and robustness of the proposed controller.