DocumentCode
700990
Title
Dynamic friction identification using neural networks
Author
Dominguez, M. ; Martinez, J.M. ; Michelin, J.M.
Author_Institution
SERMA, Commissariat a l´Energie Atomique, Gif-sur-Yvette, France
fYear
1997
fDate
1-7 July 1997
Firstpage
3306
Lastpage
3311
Abstract
This paper shows the dynamical nature of friction in an industrial high accuracy pointing device. We investigate the presence of physical effects affecting friction evolution: Dahl´s effect. Stribeck´s effect, time-lag. Friction identification is done using a nonlinear dynamical black-box scheme: neural networks. Experimental results show the good agreement between the proposed scheme and the physical friction.
Keywords
control engineering computing; delays; friction; machine control; neural nets; nonlinear control systems; Dahl effect; Stribeck effect; dynamic friction identification; industrial high accuracy pointing device; neural networks; nonlinear dynamical black-box scheme; physical effects; time-lag; Estimation; Fasteners; Force; Friction; Neural networks; Springs; Torque; Neural nets; Nonlinear dynamics; Nonlinear identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (ECC), 1997 European
Conference_Location
Brussels
Print_ISBN
978-3-9524269-0-6
Type
conf
Filename
7082622
Link To Document