Comparative Study of Trajectory Tracking Control for Automated Vehicles via Model Predictive Control and Robust H-infinity State Feedback Control

Abstract A comparative study of model predictive control (MPC) schemes and robust A state feedback control (RSC) method for trajectory tracking, is proposed in this paper. Both MPC-based and RSC-based tracking controllers are designed on the basis of a 3-DOF vehicle model, including longitudinal, lateral and yaw motions. The main objective of this paper is to compare both controllers’ performance in tracking expected trajectory under different scenarios. Therefore, three cases, namely, verification test, double lane change test and curve test, were built in Carsim-Simulink joint platform. The simulation results indicate that MPC controller performed better in terms of accuracy and responding time under well driving conditions. However, in the test of double lane change manoeuvre where the road adhesion was set as 0.2, the maximum velocity RSC can execute was 14m/s, while that for MPC was 10m/s. In addition, in the curve test, the maximum velocity MPC can carry out was only 9m/s and that for RSC was 12m/s. In conclusion, RSC was robust and stable when the driving conditions was worse, while MPC was prone to be unstable.