Sliding-mode control of a wheeled vehicle using neural network estimator

Abstract

A motion control problem of a rear-steered wheeled vehicle in consideration of the presence of uncertainties is addressed. Modeling error and additional uncertainties are taken into consideration. A sliding mode controller combining with a radial basis function neural network (RBFNN)-based estimator is proposed. The stability of the proposed control method is proven using Lyapunov stability analysis. Simulation results demonstrating the performance of the proposed control law are presented. It can be concluded that the driving velocity and steering angle performances of the proposed controllers are reasonably acceptable.