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
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;
Conference_Titel :
Control Conference (ECC), 1997 European
Conference_Location :
Brussels
Print_ISBN :
978-3-9524269-0-6
