Stiffness Adaptation and Force Regulation using Hybrid System Approach for Constrained Robots

Abstract

A new stiffness adaptation and force regulation methodology using hybrid system approach for constrained robots is presented. We present the hybrid system model and the hybrid system control synthesis for constrained robots with the stiffness uncertainties is formulated. The hybrid control approach presented has shown to be a very effective strategy to incorporate both the continuous and discrete natures of constraint motion. A nonlinear stiffness function is developed and designed to be hybrid automaton, which consists of some abstracted motion such as increase, decrease, and maintenance of stiffness. The evaluations are evaluated via experimental studies on grinding tasks. The results of experiment are showing the applicability of proposed scheme for constrained tasks.