Trajectory Tracking Control for Unmanned Vehicle Based on Nonlinear MPC in Structured Urban Roads

Abstract

In this paper, a trajectory tracking control strategy is investigated for unmanned vehicles operating on structured urban roads under multiple constraints. A hierarchical control framework is developed to coordinate lateral steering and longitudinal velocity for accurate trajectory tracking. For the lateral layer, a nonlinear model predictive controller is proposed to optimize the steering angle under steering angle, steering increment, and terminal constraints. A prediction stride strategy is introduced to extend the prediction range while keeping the number of prediction nodes unchanged, and an augmented terminal formulation is developed to account for the curved path equilibrium and steering increment constraint. For the longitudinal layer, a PID controller is employed to track the desired velocity profile, together with a data-driven actuator calibration method for longitudinal control implementation. The nominal recursive feasibility on the internal prediction grid and the local asymptotic stability of the terminal system are established. Simulation and real vehicle results demonstrate the effectiveness of the proposed hierarchical control strategy under low-speed urban road conditions.