Research on unmanned vehicle trajectory tracking control strategy based on model predictive control

Abstract:
Aiming at the problem of trajectory tracking of unmanned vehicles, a trajectory tracking control strategy based on model predictive control (MPC) has been proposed. First, the nonlinear kinematic equations of the unmanned vehicle are linearized to establish a linear tracking error model for the unmanned vehicle. Secondly, the trajectory tracking controller is designed by combining linear MPC theory and adding soft constraints on tire side deflection angle. Finally, a joint Simulink/Carsim simulation platform is established to compare and analyze the tracking effects of two control strategies, LQR and MPC, and the experiments track the reference circle and the reference straight line respectively under the condition of interference using different vehicle speeds. The simulation results show that the proposed control strategy has better trajectory tracking performance, smaller tracking error and better anti-interference ability under highspeed conditions.