Comparison of EKBF-based and Classical Friction Compensation

Abstract

In servo control, traditionally, models that attempt to capture the friction-velocity curve and interactions at contacting surfaces have been used to compensate for friction-introduced tracking errors. Recently, however, extended Kalman-Bucy filter (EKBF)-based approaches that do not use a phenomenological or structured model for friction have been proposed. In addition to being cast as a friction estimator, the EKBF can also be used to provide parameter adaptation for simple friction models. In this paper, a traditional motor-driven inertia experiment is used to demonstrate the usefulness of EKBF in friction compensation. In addition, a numerical simulation is used to test the robustness of the new methods to normal force variations. Using root mean square position tracking error as the performance metric, comparisons to traditional model-based approaches are provided.