基于自适应模型预测控制的高速行驶工况下车辆轨迹跟踪控制

Vehicle Trajectory Tracking Control under High-Speed Driving Conditions Based on Adaptive Model Predictive Control

为保证智能车辆在不同附着系数路面上高速行驶时轨迹跟踪的精度和操纵稳定性,利用自适应模型预测控制(AMPC)方法对轮胎侧偏刚度进行在线估算并对高速行驶工况下的车辆动力学模型参数进行实时更新,采用不定步长(NFS)离散化方法延长预测时域,同时将滑移稳定性约束加入目标函数,从而在高速行驶工况下保持较高的稳定性和控制实时性。CarSim与MATLAB/Simulink联合仿真结果表明,所提出的方法可提高高速工况下车辆在不同附着系数路面上行驶时的操纵稳定性,并获得较高的控制精度。

In order to ensure the accuracy of trajectory tracking and maneuvering stability of intelligent vehicles at high speeds on roads with different coefficients of adhesion,the Adaptive Model Predictive Control(AMPC)method was used to estimate the tire cornering stiffness on-line and update the parameters of the vehicle dynamics model in real time under highspeed driving conditions,and the Non-Fixed Step(NFS)discrete method was used to prolong the prediction time domain while the slip stability constraints were added into the objective function,thus maintaining high stability and control in real time under high-speed driving conditions.The proposed method can improve the maneuvering stability and control accuracy when the vehicle is driving on the road with different adhesion coefficients under high-speed driving conditions,as shown in the joint simulation results of CarSim and MATLAB/Simulink.