Trajectory Tracking for Autonomous Multi-Axle Vehicles Based on Linear Quadratic Regulator

To enhance the precision of trajectory tracking for an intelligent vehicle driven by a multi-axle wheel hub motor, a lateral control strategy based on the linear quadratic regulator (LQR) is proposed. First, a two-degrees-of-freedom dynamics model of the four-wheeled vehicle and a trajectory tracking error model are established. Second, a trajectory tracking controller employing the lateral LQR control algorithm is designed, while the longitudinal velocity is controlled using a PID controller. Furthermore, direct yaw moment control is incorporated to enhance the control precision and stability during trajectory tracking. Through joint simulations in TruckSim and Simulink under both low-speed and high-speed conditions, the control algorithm is evaluated. The simulation results demonstrate that the control algorithm is capable of effectively conducting joint simulation experiments under various operational scenarios. It accurately follows the predefined path model, maintaining a tracking distance deviation of less than 0.18 m, a yaw rate of under 14.5 degrees per second, and a lateral deviation angle of less than 3 degrees. This algorithm exhibits excellent trajectory tracking precision and a commendable level of stability.