Research on Model Predictive Control-based Trajectory Tracking for Unmanned Vehicles

In this paper, the unmanned vehicle trajectory tracking problems were studied. In order to improve the stability of unmanned vehicles, the trajectory tracking control algorithm based on model predictive control (MPC) algorithm was researched by adding the dynamic constraints of centroid, acceleration and tire side angle on the basis of vehicle dynamics model. The trajectory planning layer was established on top of the trajectory tracking control layer, and the Carsim/Simulink simulation platform was built. At different speeds and under different road adhesion conditions, the algorithm was verified and compared. The simulation results showed that the model predictive control algorithm with dynamic constraints was provided with excellent tracking performance under severe conditions and well adaptive to environment interference.