Indirect fuzzy adaptive model-following control for robot manipulators

Abstract

This paper investigates fuzzy approach to the adaptive control of robot manipulators. Adaptive fuzzy systems are trained to approximate the robot dynamic; then, based on the estimated model, a certainty equivalent control is designed to ensure the tracking of a stable reference model. It is proven, using Lyapunov stability, that this adaptive scheme is robust against uncertainty, external disturbance and approximation error, and achieves asymptotic tracking of a stable reference model. The effectiveness of the proposed fuzzy approach is demonstrated, by simulation, on a two-link robot model.