Application of wavelet networks to adaptive control of robotic manipulators

Abstract

In this paper, a wavelet-based adaptive control is proposed for a class of robotic manipulators, which consist of nonlinearities for friction effects and uncertain terms as disturbances. The controller is calculated by using a mixed of feedback linearization technique, supervisory control and H ∞ control. In addition, the parameter adaptive laws of the wavelet network are developed using a Lyapunov-based design. It is also shown that both system tracking stability and convergence of the error estimation can be guaranteed in the closed-loop system. Simulation results on a three-link robot manipulator show the satisfactory performance of the proposed control schemes even in the presence of large modeling uncertainties and external disturbances. © 2011 Springer-Verlag.