Friction compensation of the electromechanical drive systems using neural networks

Kazuo Kiguchi, Hermann Henrichfreise, Karl Peter Hesseler

研究成果: Contribution to conferencePaper査読

3 被引用数 (Scopus)

抄録

Friction is an undesired phenomenon in many mechanical systems. Feedforward of a suitable estimate of friction is an effective method to compensate for the friction-dependent position errors in the steady state. It is not easy, however, to make a precise friction model because of the complexity of static and dynamic characteristics of friction such as the Stribeck effect, the Dahl effect, stick-slip motion, and so on. In this paper, we propose an effective friction compensation method for the electromechanical drive systems. In the proposed method, neural networks are applied in parallel to a linear observer, for the electromechanical positioning system (EMPS) which is used at the Cologne Laboratory of Mechatronics (CLM) at the University of Applied Sciences Cologne for experimental investigation of position control schemes for compliant systems with friction.

本文言語英語
ページ1758-1762
ページ数5
DOI
出版ステータス出版済み - 12 1 2004
外部発表はい
イベントIECON 2004 - 30th Annual Conference of IEEE Industrial Electronics Society - Busan, 大韓民国
継続期間: 11 2 200411 6 2004

その他

その他IECON 2004 - 30th Annual Conference of IEEE Industrial Electronics Society
国/地域大韓民国
CityBusan
Period11/2/0411/6/04

All Science Journal Classification (ASJC) codes

  • 制御およびシステム工学
  • 電子工学および電気工学

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