Adaptive Backstepping robust control based on RBF neural network for a military robot system

被引：0

作者：

Xie Xiao-zhu ^{[1
]}

Hou Bing ^{[2
]}

Cui Weining ^{[1
]}

Yu Lixin ^{[1
]}

机构：

[1] Acad Armored Force Engn, Dept Informat Engn, Beijing 100072, Peoples R China

[2] Minist Elect Engn & Informat Sci, Gen Armament Dept, Beijing 100034, Peoples R China

来源：

ICFCSE 2011: 2011 INTERNATIONAL CONFERENCE ON FUTURE COMPUTER SUPPORTED EDUCATION, VOL 2 | 2011年

关键词：

radial basis function; neural network; adaptive control; backstepping control;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Based on adaptive backstepping approach and RBF neural network theory, a robust controller is designed for a military robot system with uncertainty and unknown parameter. The controller expression with undermined parameters can be acquired by using adaptive backstepping design idea, and the controller parameters are adjusted online by using RBF neural network. The simulation result shows that the controller is robust to nonlinear system and can guarantee the globe boundness of all closed-loop signals.

引用

页码：318 / 321

页数：4