{"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}
引用次数: 0
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.