Integrating Trajectory Tracking and Stability Control Strategy for Autonomous Four-Wheel-Drive

This research introduces a lateral control algorithm for Autonomous Four-Wheel-Drive vehicles that integrates trajectory tracking with stability control, significantly enhancing trajectory tracking performance under extreme operating conditions. Based on the multi-objective optimization capabilities of Model Predictive Control (MPC), an objective function was formulated to minimize lateral error and yaw rate error, simultaneously optimizing the steering angle and additional yaw moment outputs. This approach effectively integrates trajectory tracking and stability control into a single controller, simplifying the traditional decentralized control structure and achieving a balanced optimization between tracking accuracy and driving stability. Following this, simulation experiments are conducted to validate the effectiveness of the presented control system to improve both tracking accuracy and vehicular stability. When compared to alternative algorithms which deduce the additional yaw moment based on sliding mode control, the introduced algorithm demonstrates substantial improvements, with a 25% reduction in lateral tracking error and a 14<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> decrease in heading error, thus ensuring the enhanced stability of vehicular operations.