Friction compensation of the electromechanical drive systems using neural networks

Kazuo Kiguchi, Hermann Henrichfreise, Karl Peter Hesseler

Research output: Contribution to conferencePaperpeer-review

5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages1758-1762
Number of pages5
DOIs
Publication statusPublished - Dec 1 2004
Externally publishedYes
EventIECON 2004 - 30th Annual Conference of IEEE Industrial Electronics Society - Busan, Korea, Republic of
Duration: Nov 2 2004Nov 6 2004

Other

OtherIECON 2004 - 30th Annual Conference of IEEE Industrial Electronics Society
Country/TerritoryKorea, Republic of
CityBusan
Period11/2/0411/6/04

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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