Nonlinear robust wheel slip rate tracking control for autonomous vehicle with actuator dynamics

Abstract

This article presents a novel nonlinear robust wheel slip rate tracking control strategy for autonomous vehicle with actuator dynamics. First, a simple yet effective wheel slip rate dynamic model with the lumped uncertainty is established as the basis of the nonlinear robust wheel slip rate tracking control strategy design. Second, a nonlinear robust wheel slip rate tracking control law with lumped uncertainty observer is derived via the Lyapunov-based method. The lumped uncertainty observer is used to estimate and compensate the lumped uncertainty of the system by combining the radial basis function neural network with the adaptive laws for the unknown optimal weight vector of the radial basis function neural network. Then, a novel tracking differentiator is designed to calculate the derivative of the desired wheel slip rate, which is an essential aspect of the proposed nonlinear robust wheel slip rate tracking control law. Finally, the performance of the proposed control strategy is verified based on straight line braking maneuvers with three typical signals.