Abstract: Aiming at the problem that the tracking accuracy of unmanned vehicles in trajectory tracking control decreases due to imprecision of the model and internal and external interference, this paper proposes a control algorithm combining model predictive control (MPC) and improved active disturbance rejection control compensation. Firstly, an MPC controller is established. In order to improve the real-time performance of the calculation, a nonlinear model predictive control is transformed into linear time-varying model predictive control. Due to trajectory deviations caused attributed to the inaccuracy of the model and internal and external disturbance, a smoother nonlinear function is constructed, and then the improved active disturbance rejection control is designed. With the lateral deviation and the angular deviation tending to be zero as the goal to compensate the front wheel angles of the vehicle, this paper enhances the unmanned vehicle trajectory tracking performance and anti-jamming performance. The simulation results under different working conditions show that this method effectively completes trajectory tracking with small tracking deviations, and has strong robustness to external interference and vehicle parameter change.