The trajectory tracking control strategy for intelligent vehicle is proposed in this article. Considering the parameters perturbations and external disturbances of the vehicle system, based on the vehicle dynamics and the preview follower theory, the lateral preview deviation dynamics model of the vehicle system is established which uses lateral preview position deviation, lateral preview velocity deviation, lateral preview attitude angle deviation, and lateral preview attitude angle velocity deviation as the tracking state variables. For this uncertain system, the adaptive sliding mode control algorithm is adopted to design the preview controller to eliminate the effects of uncertainties and realize high accuracy of the target trajectory tracking. According to the real-time deviations of lateral position and lateral attitude angle, the feedback controller is designed based on the fuzzy control algorithm. For improving the adaptability to the multiple dynamic states, the extension theory is introduced to design the coordination controller to adjusting the control proportions of the preview controller and the feedback controller to the front wheel steering angle. Simulation results verify the adaptability, robustness, accuracy of the control strategy under which the intelligent vehicle has good handling stability.

中文翻译：

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智能车辆自适应轨迹跟踪控制策略

本文提出了智能车辆的轨迹跟踪控制策略。考虑车辆系统的参数扰动和外部扰动，基于车辆动力学和预视跟随理论，建立了车辆系统的侧向预检偏差动力学模型，该模型采用侧向预视位置偏差、侧向预视速度偏差、侧向预视姿态。角偏差，横向预览姿态角速度偏差作为跟踪状态变量。针对该不确定系统，采用自适应滑模控制算法设计预览控制器，消除不确定因素的影响，实现目标轨迹的高精度跟踪。根据横向位置和横向姿态角的实时偏差，反馈控制器是基于模糊控制算法设计的。为提高对多动态状态的适应性，引入可拓理论设计协调控制器，调整前驱控制器和反馈控制器对前轮转向角的控制比例。仿真结果验证了控制策略的适应性、鲁棒性和准确性，智能车辆具有良好的操纵稳定性。