{"title":"A Robust Sliding Mode Control With RBFNN Compensation For Uncertain Networked Control System","authors":"Liman Yang, Yunhua Li, Li Zuo","doi":"10.1109/RAMECH.2008.4681512","DOIUrl":null,"url":null,"abstract":"For the uncertain NCS with stochastic network delay less than one period, a sort of RBFNN-DSMC algorithm combining discrete sliding mode control and RBF neural network is presented. In view of the coupling influence of time-variable delay and plant model error as well as exterior disturbance, RBFNN is used to approach the equivalent disturbance online and output assistant control quantity so as to restrain uncertainty with the discrete sliding mode controller with delay compensation together. Simulation study indicates that the above-mentioned algorithm has good control performance and robustness for the uncertain NCS.","PeriodicalId":320560,"journal":{"name":"2008 IEEE Conference on Robotics, Automation and Mechatronics","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE Conference on Robotics, Automation and Mechatronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RAMECH.2008.4681512","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
For the uncertain NCS with stochastic network delay less than one period, a sort of RBFNN-DSMC algorithm combining discrete sliding mode control and RBF neural network is presented. In view of the coupling influence of time-variable delay and plant model error as well as exterior disturbance, RBFNN is used to approach the equivalent disturbance online and output assistant control quantity so as to restrain uncertainty with the discrete sliding mode controller with delay compensation together. Simulation study indicates that the above-mentioned algorithm has good control performance and robustness for the uncertain NCS.