Fuzzy selection of fuzzy-neuro robot force controllers in an unknown environment

Abstract

In this paper, an effective control policy for robot contact tasks with an unknown environment is proposed using fuzzy-neural techniques. In this control policy, a neural network is applied to classify the unknown environment based on its dynamic response and then fuzzy selector selects the suitable fuzzy neural force controllers. The selected fuzzy neural force controllers are able to realize the desired contact force precisely using their online adaptation ability. The fuzzy selection of controllers realize force control with the environment whose suitable fuzzy neural force controller is not prepared. The effectiveness of the proposed method is evaluated by experiment with a 2-DOF planar robot manipulator.