A Model Predictive Control with Preview-Follower Theory Algorithm for Trajectory Tracking Control in Autonomous Vehicles

Research on trajectory tracking is crucial for the development of autonomous vehicles. This paper presents a scheme by utilizing model predictive control (MPC) and preview-follower theory (PFT), which includes reference generation module MPC controller. The could calculate lateral acceleration at preview point PFT to update state variables, generate yaw rate in each prediction point. Since range increased, makes calculation more accurate. Through physical constraints, controller can achieve best path. problem formulated as linear time-varying (LTV) from nonlinear vehicle dynamics continuous online linearization. MPC-PFT method performs well increasing effective length Compared with controllers, effectiveness robustness proposed are proved simulations two typical working conditions.