NON-LOCAL HYSTERESIS FUNCTION IDENTIFICATION AND COMPENSATION WITH NEURAL NETWORKS

Abstract

This paper discusses the on-line identification of non-local static hysteresis functions, which are encountered in mechanical friction, magnetic materials, and piezoelectric actuators and cause problems by the design of controllers. In this article we want to introduce a compensation method for friction in presliding regime, based on the simplified Leuven Friction Model and on technology borrowed from neural networks. We present a solution how to identify the hysteresis caused by the friction, and how to use this identified model for the compensation of the friction effects. Results from both simulations and experiments will be shown.