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考虑横纵向误差协调的智能汽车路径跟踪控制研究
引用本文:秦雪帅,王旭东.考虑横纵向误差协调的智能汽车路径跟踪控制研究[J].重庆工商大学学报(自然科学版),2024(1):82-90.
作者姓名:秦雪帅  王旭东
作者单位:重庆工商大学 机械工程学院,重庆 400067
摘    要:针对传统轨迹跟踪控制方法应用场景局限,精度不高的问题,为实现车辆横纵向联合控制从而提升无人驾 驶汽车在结构化场景下的轨迹跟踪效果,本文建立了自然坐标系下的车辆跟踪误差模型,设计基于 LQR 与 PID 相 结合的车辆横纵向耦合控制器。 在横向控制层面,为消除系统稳定误差,通过引入前馈控制量实现系统的整体稳 定,减小车辆在实际运行过程中产生的横向误差,提升控制过程的稳定性;在纵向控制层面,运用 PID 控制策略进 行调节,实现车辆的实际速度与规划速度,实际位置与规划位置之间的精确匹配。 通过 MATLAB / Simulink 与 Carsim 搭建联合仿真平台,针对日常泊车、驶入主路以及超车多种工况进行仿真验证。 仿真结果表明:本文所设计 的横纵向联合控制器将车辆的轨迹跟踪误差控制在可接受范围之内的同时,轨迹跟踪效果满足乘客对车辆乘坐舒 适性的要求,故本文设计的控制器具备一定的稳定性和准确性。

关 键 词:智能汽车  跟踪控制  线性二次调节  PID  联合仿真

Research on Intelligent Vehicle Path Tracking Control Considering Transverse-Longitudinal Error Coordination
QIN Xueshuai,WANG Xudong.Research on Intelligent Vehicle Path Tracking Control Considering Transverse-Longitudinal Error Coordination[J].Journal of Chongqing Technology and Business University:Natural Science Edition,2024(1):82-90.
Authors:QIN Xueshuai  WANG Xudong
Institution:School of Mechanical Engineering, Chongqing Technology and Business University, Chongqing 400067, China
Abstract:The traditional trajectory tracking control method is limited in application scenarios and has low accuracy. In order to realize the vehicle transverse and longitudinal joint control and improve the trajectory tracking effect of unmanned vehicles in structured scenarios this paper established the vehicle tracking error model under the natural coordinate system and designed the vehicle transverse and longitudinal coupling controller based on the combination of LQR and PID. At the transverse control level in order to eliminate the stability error of the system the introduction of the feedforward control quantity realized the overall stability of the system reducing the transverse error generated during the actual operation of the vehicle and improving the stability of the control process. At the longitudinal control level a PID control strategy was used to achieve an accurate match between the actual speed and the planned speed and between the actual position and the planned position of the vehicle. A joint simulation platform was built by MATLAB / Simulink and Carsim to verify various conditions such as daily parking driving into the main road and overtaking. The simulation results showed that the transverse-longitudinal joint controller designed in this paper could control the trajectory tracking error of the vehicle within an acceptable range and the trajectory tracking effect could meet passengers?? requirements for vehicle comfort. Therefore the controller designed in this paper has certain stability and accuracy.
Keywords:intelligent vehicle  tracking control  linear quadratic regulation  PID  joint simulation
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