Fourier series-based adaptive tracking control for robot manipulators

Abstract

This paper presents a Fourier series-based adaptive trajectory tracking controller for uncertain robotic manipulators. The desired trajectories to be tracked are assumed to be smooth and periodic with known period. Fourier series expansion is used to approximate robotic system uncertainties. The Fourier coefficients adaptation law is driven by the identification error and it is obtained from the Lyapunov approach. Simulation results for a two-link robot manipulator are provided to show the effectiveness of the proposed adaptive controller.