微型电脑应用2025，Vol.41Issue(1)：1-5,5.
基于模型预测控制的虚拟轨道列车转向控制方法
A Steering Control Method for Virtual Rail Trains Based on Model Predictive Control
摘要
Abstract
The virtual rail train is a three-unit,double-articulated,all-axle steering rubber wheel train.The steering controller obtains the vehicle state through the sensor and controls the steering angle of each axis to suppress the backward amplification effect caused by the hinged structure and ensure that the train runs along the preset track.Due to the all-axle steering system,the existence of multiple inputs and complex dynamic constraints,as well as the motion interference between cars,the control methods of ordinary passenger cars are no longer suitable.Therefore,the steering controller needs to consider the dynamic characteristics of articulated vehicles to realize the coordinated control of all axes.This paper presents a time-varying linear model predictive control method for all-axle steering control of virtual track trains,which uses dynamic model to predict,in or-der to improve the prediction accuracy under various working conditions and ensure the smoothness of steering and ride com-fort.In view of the high nonlinear degree of the dynamic model,the online linearization method near by the operating point is used to accelerate the solution.The co-simulation results of MATLAB and TruckMaker software show that the proposed con-trol method is better than the method based on extended Ackermann steering,and is similar to the nonlinear model predictive controller,but the calculation speed is faster.After acceleration,the controller can achieve a control frequency of 20 Hz to meet the real-time control requirements.关键词
模型预测控制/全轴转向系统/虚拟轨道列车/在线线性化Key words
model predictive control/all-wheel steering system/virtual rail train/online linearization分类
信息技术与安全科学引用本文复制引用
刘汉,侯成滨,戴靖雯,沙睿芝,束展逸,罗茂臻..基于模型预测控制的虚拟轨道列车转向控制方法[J].微型电脑应用,2025,41(1):1-5,5.基金项目
国家自然科学基金面上项目(62373284) （62373284）
