{"title":"基于神经网络的高阶非线性延迟系统自适应控制设计","authors":"Jimin Yu, Baohua Wu, Shangbo Zhou","doi":"10.1109/ICCECT.2012.147","DOIUrl":null,"url":null,"abstract":"This paper focuses on the control of high-order nonlinear time-delay systems in block-triangular form. The RBF NN (radial basis function neural network) is chosen to approximate the unknown nonlinear functions in the system dynamics. Lyapunov-Krasovskii functionals are used to compensate the influence of delay terms. Then an adaptive neural network output tracking controller is designed by using the back-stepping recursive method. Based on Lyapunov stability theory and Theorem 1, the proposed controller can guarantee all closed-loop signals are globally, uniformly and ultimately bounded, which is proved, while the output tracking converges to a neighborhood of the origin. Finally, a simulation example is given to illustrate the correctness of the theoretical results.","PeriodicalId":153613,"journal":{"name":"2012 International Conference on Control Engineering and Communication Technology","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive Control Design for Higher Order Nonlinear Delay Systems Based on Neural Network\",\"authors\":\"Jimin Yu, Baohua Wu, Shangbo Zhou\",\"doi\":\"10.1109/ICCECT.2012.147\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper focuses on the control of high-order nonlinear time-delay systems in block-triangular form. The RBF NN (radial basis function neural network) is chosen to approximate the unknown nonlinear functions in the system dynamics. Lyapunov-Krasovskii functionals are used to compensate the influence of delay terms. Then an adaptive neural network output tracking controller is designed by using the back-stepping recursive method. Based on Lyapunov stability theory and Theorem 1, the proposed controller can guarantee all closed-loop signals are globally, uniformly and ultimately bounded, which is proved, while the output tracking converges to a neighborhood of the origin. Finally, a simulation example is given to illustrate the correctness of the theoretical results.\",\"PeriodicalId\":153613,\"journal\":{\"name\":\"2012 International Conference on Control Engineering and Communication Technology\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Control Engineering and Communication Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCECT.2012.147\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Control Engineering and Communication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCECT.2012.147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive Control Design for Higher Order Nonlinear Delay Systems Based on Neural Network
This paper focuses on the control of high-order nonlinear time-delay systems in block-triangular form. The RBF NN (radial basis function neural network) is chosen to approximate the unknown nonlinear functions in the system dynamics. Lyapunov-Krasovskii functionals are used to compensate the influence of delay terms. Then an adaptive neural network output tracking controller is designed by using the back-stepping recursive method. Based on Lyapunov stability theory and Theorem 1, the proposed controller can guarantee all closed-loop signals are globally, uniformly and ultimately bounded, which is proved, while the output tracking converges to a neighborhood of the origin. Finally, a simulation example is given to illustrate the correctness of the theoretical results.