Adaptive-neural control of a class of unknown nonlinear discrete-time systems

被引：0
|
作者：
Horng, JH [1 ]
机构：
[1] Natl Taiwan Ocean Univ, Dept Mech & Marine Engn, Keelung 20224, Taiwan
来源：
SICE '98 - PROCEEDINGS OF THE 37TH SICE ANNUAL CONFERENCE: INTERNATIONAL SESSION PAPERS | 1998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, an adaptive controller based on neural networks is derived for controlling a class of unknown nonlinear discrete-time systems. The learning algorithm, Widrow-Hoff delta rule, is used to minimize the error signal. It is proved that the control objective is achieved by the closed-loop system and that the system remains closed-loop stability. The effectiveness of the proposed control scheme is also demonstrated by a simulation example.
引用
收藏
页码：1067 / 1070
页数：4
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