Neural network based friction compensation in motion control

Frictional uncertainties are known to be a major cause of performance degradation in motion control systems. Artificial neural network based modelling and compensation of nonlinear friction in direct drive servo mechanisms have been investigated. The proposed method is successfully tested experimentally on a direct-drive single-link arm and its performance is compared to different friction modelling techniques.