Robust tracking control of uncertain nonholonomic wheeled mobile robot incorporating the actuator dynamics

Abstract

In this paper, robust tracking control is studied for uncertain nonholonomic wheeled mobile robot (WMR) incorporating the actuator dynamics with unknown external disturbances. Using the radial basis function (RBF) NNs to approximate the unknown closed-loop system dynamics and adopting an adaptive sliding mode feedback term to compensate for the approximation errors as well as the external disturbances, a robust adaptive neural network controller is designed. The stability of the closed-loop system and the asymptotical convergence of tracking errors are proved via Lyapunov stability theory. Meanwhile, the convergence of NN weights is testified and the converged/constant weights can be recycled to reach stability and improve performance. Finally, simulations are presented to demonstrate the effectiveness of the proposed control scheme.