A Model-following Adaptive Controller for Linear/Nonlinear Plants using Radial Basis Function Neural Networks

被引：0
|
作者：
Masukake, Yuichi [1 ]
Ishida, Yoshihisa [1 ]
机构：
[1] Meiji Univ, Grad Sch Elect Engn, Tokyo 101, Japan
来源：
PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 26, PARTS 1 AND 2, DECEMBER 2007 | 2007年 / 26卷
关键词：
Linear/nonlinear plants; neural networks; radial basis function networks;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, we proposed a method to design a model-following adaptive controller for linear/nonlinear plants. Radial basis function neural networks (RBF-NNs), which are known for their stable learning capability and fast training, are used to identify linear/nonlinear plants. Simulation results show that the proposed method is effective in controlling both linear and nonlinear plants with disturbance in the plant input.
引用
收藏
页码：407 / +
页数：2
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