Adaptive proportional derivative lateral longitudinal integrated automatic lane keeping control strategy based on finite time disturbance observer

For distributed drive electric vehicles, designing an effective automatic lane keeping system and optimizing wheel torque allocation to enhance overall performance have consistently been a key research focus in this field. However, such systems face multiple challenges in practical applications, including external disturbances and strong coupling in vehicle dynamics, which result in not only limited tracking accuracy with traditional control methods but also difficulty in simultaneously and effectively suppressing both matched and unmatched disturbances. To address the aforementioned issues, this study designs an integrated lateral-longitudinal control strategy that combines a finite time disturbance observer (FTDO) with adaptive proportional-derivative (APD) control. This strategy utilizes the FTDO to achieve rapid and accurate estimation and compensation of various disturbances, while the APD control enables online real-time adjustment of controller parameters. Simulation results demonstrate that under various complex operating conditions, the proposed method effectively improves lane-keeping accuracy, with its lateral tracking performance outperforming that of linear model predictive control (MPC) and non-singular terminal sliding mode control (NTSMC). The composite control framework exhibits both favorable robustness and high precision, thereby providing a more promising solution for the development of future autonomous driving systems.