A Robust Sliding Mode Control With RBFNN Compensation For Uncertain Networked Control System

被引:0
|
作者
Yang, Liman [1 ]
Li, Yunhua [1 ]
Zuo, Li [2 ]
机构
[1] Beijing Univ Aeronaut & Astronaut, Sch Automat Sci & Elect Engn, Beijing 100083, Peoples R China
[2] Beijing Inst Petrochem Technol, Dept Elect Engn, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
networked control system; sliding mode control; RBF neural network; delay; disturbance;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1043 / +
页数:2
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