A learning algorithm for hybrid force control of robot arms

Abstract

An investigation of the hybrid force control of robot arms by learning is presented. A force control scheme based on feedback linearization is used to build an algorithm that improves, trial by trial, force and position tracking over a finite time interval. Unlike other published learning control schemes, the proposed algorithm does not rely on high-gain feedback. Robustness and convergence in spite of sufficiently small system parameter uncertainties and disturbances is proved by means of the contraction mapping principle.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>