Longitudinal Velocity Tracking Control of a 4WID Electric Vehicle

A novel four-wheel independent drive (4WID) electric vehicle (EV) is proposed as an autonomous ground vehicle (AGV) in this paper. Since longitudinal motion control is the fundamental problem of autonomous vehicle control, a traditional sliding mode control (SMC) algorithm and an improved adaptive sliding mode control (ASMC) algorithm using Radial Basis Function (RBF) neural network are applied to longitudinal velocity tracking controller design. To evaluate the performance of the designed controllers for the 4WID EV, two simulation maneuvers are carried out including straight line condition and single lane-change condition. The simulation results indicate that the longitudinal velocity tracking controller using ASMC has smaller tracking error and better disturbance rejection performance than SMC.