A model-free decentralized control for robot manipulators

Abstract

A model-free robust/adaptive decentralized controller for nonlinear uncertain robot manipulators is presented. The proposed controller consists of a PD controller, a robust/adaptive controller and dynamic compensator. The dynamic compensator is online up-dated based on the Taylor expansion in terms of the historical information of the individual local inputs to the system. The result obtained from the dynamic compensator is used to cancel the nonlinearity and uncertainties within the system to be controlled. The robust/adaptive controller is used to handle the effect of the residual dynamics, which is the difference of the dynamics of the system and the estimated one. The stability analysis of the closed-loop system is performed based on a modified version of Lyapunov's theory. Experimental results on the tracking control of a 3-DOF direct drive robot are presented for illustration.