Neural network based friction compensation in motion control

被引：13
|
作者：
Ciliz, MK [1 ]
Tomizuka, M
机构：
[1] Bogazici Univ, Dept Elect Engn, TR-80815 Bebek, Istanbul, Turkey
[2] Univ Calif Berkeley, Dept Mech Engn, Berkeley, CA 94720 USA
来源：
ELECTRONICS LETTERS | 2004年 / 40卷 / 12期
关键词：
D O I：
10.1049/el:20040500
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Frictional uncertainties are known to be a major cause of performance degradation in motion control systems. Artificial neural network based modelling and compensation of nonlinear friction in direct drive servo mechanisms have been investigated. The proposed method is successfully tested experimentally on a direct-drive single-link arm and its performance is compared to different friction modelling techniques.
引用
收藏
页码：752 / 753
页数：2
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