Title :
Modeling and compensation of frictional uncertainties in motion control: a neural network based approach
Author :
Ciliz, M. Kemal ; Tomizuka, Masayoshi
Author_Institution :
Dept. of Electr. Eng., Bogazici Univ., Istanbul, Turkey
Abstract :
Frictional uncertainties are known to be a major cause of performance degradation in motion control systems. This paper investigates the modeling and compensation of nonlinear friction dynamics in direct drive servo mechanisms. Different modeling techniques such as, model based adaptive identification, modeling based on experimental data and neural network based approximation are discussed and experimentally tested on the first link of a direct drive manipulator
Keywords :
compensation; friction; manipulators; motion control; neural nets; servomechanisms; compensation; direct drive manipulator; direct drive servo mechanisms; frictional uncertainties; model based adaptive identification; motion control systems; neural network based approach; neural network based approximation; nonlinear friction dynamics; performance degradation; Artificial neural networks; Degradation; Friction; Intelligent networks; Mechanical engineering; Motion control; Neural networks; Parametric statistics; Servomechanisms; Uncertainty;
Conference_Titel :
American Control Conference, Proceedings of the 1995
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2445-5
DOI :
10.1109/ACC.1995.532207
