Robust model reference adaptive control of robots based on neural network parametrization

被引：0
|
作者：
Ge, SS
Lee, TH
机构：
来源：
PROCEEDINGS OF THE 1997 AMERICAN CONTROL CONFERENCE, VOLS 1-6 | 1997年
关键词：
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：
In this paper, a robust model reference adaptive controller is presented for robots based on neural network parametrization. The controller is based on applying direct adaptive techniques to a basic fixed controller for better control performance, while a sliding mode control is introduced to guarantee robust closed-loop stability. It is shown that if Bounded Basis Function (BBF) networks are used for the parallel NN, uniformly stable adaptation is assured and asymptotic tracking of the reference signal is achieved.
引用
收藏
页码：2006 / 2010
页数：5
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