智能汽车轨迹跟踪综合控制策略  

Integrated Trajectory Tracking Control Strategy for Intelligent Vehicles

作　　者：高峰 冯樱 杨烜 何建彪 Gao Feng;Feng Ying;Yang Xuan;He Jianbiao(School of Automotive Engineering,Hubei University of Automotive Technology,Shiyan 442002,China)

机构地区：[1]湖北汽车工业学院汽车工程学院,湖北十堰442002

出　　处：《湖北汽车工业学院学报》2025年第1期1-8,共8页Journal of Hubei University Of Automotive Technology

基　　金：中央引导地方科技发展专项(2019ZYYD019)。

摘　　要：为提高智能汽车轨迹跟踪的控制精度和行驶稳定性,提出一种综合横向和纵向的轨迹跟踪控制策略。横向采用自适应模型预测控制,利用递归最小二乘算法实时估计轮胎侧偏刚度,分析预测时域和控制时域参数对模型预测控制器的影响,建立评价指标来判断轨迹跟踪控制的效果;纵向采用双PID控制,减小期望车速与实际车速的差值;实现横向方向盘转角和纵向速度综合控制,通过Simulink和CarSim在不同车速和路面附着系数工况下进行仿真验证。结果表明:自适应模型预测控制能有效降低横向偏差,提出的控制策略可实现精确跟踪。In order to improve the trajectory tracking control accuracy and driving stability of intelligent vehicles,a trajectory tracking control strategy combining lateral and longitudinal directions was proposed.The adaptive model predictive control was used for the lateral direction,and the recursive least squares algorithm was used to estimate the tire cornering stiffness in real time.The influence of the prediction time domain and the control time domain parameters on the model predictive controller was analyzed,and the evaluation index was established for assessing trajectory tracking control.Double proportion-integration-differentiation(PID) control was used in the longitudinal direction to reduce the difference between the expected speed and the actual speed.The integrated control of lateral steering wheel angle and longitudinal speed was realized,and simulation verification was carried out by Simulink and CarSim under different vehicle speeds and road adhesion coefficients.The experimental results show that the adaptive model predictive control can effectively reduce the lateral deviations,and the proposed control strategy can achieve accurate tracking.

关 键 词：参数估计 自适应模型预测控制 时域参数 

分 类 号：U463.6[机械工程—车辆工程]