自适应LOS制导结合MPC控制的车辆循迹优化

Vehicle tracking optimization based on adaptive LOS guidance and MPC control

摘要:

为提升无人驾驶车辆循迹过程的动态响应能力,确保车辆能快速且稳定地跟踪参考路线,首先基于模糊控制的思想,在传统视线（line-of-sight,LOS）制导策略中引入了时变前视距离,提出了改进后的自适应LOS制导策略,把目标轨迹的跟踪简化为目标点航向的跟踪。其次,建立车辆三自由度动力学模型,并结合自适应LOS状态方程设计路径跟踪系统的线性数学模型。最后,基于模型预测原理,使用多步预测、滚动实时优化、反馈校正等控制方式,求解出最优反馈的方向盘控制指令。本文为验证上述所提及跟踪策略的有效性,在Simulink仿真环境中分别以直线路径和曲线路径作为参考轨迹进行追踪仿真实验,结果表明:所提自适应LOS制导策略能使循迹车辆的轨迹横向误差和航向误差迅速地收敛到零,从而验证了改进LOS制导算法可以提高无人车路径跟踪的响应速度和平稳性。

Abstract:

To improve the dynamic response ability of unmanned vehicle tracking process and ensure that the vehicle can track the reference route quickly and stably, this paper firstly introduces the time-varying forward-looking distance into the traditional line-of-sight (LOS)guidance strategy based on the idea of fuzzy control, and proposes the improved adaptive LOS guidance strategy, which simplifies the tracking of target trajectory to the heading of the target point track. Secondly, a three degree of freedom dynamic model of vehicle is established, and the linear system mathematical model of path tracking is designed by combining the tracking error variable of adaptive LOS. Finally, multi-step prediction, rolling real-time optimization and feedback correction are used to solve the optimal feedback steering wheel control command, based on the principle of model prediction. To verify the effectiveness of the above-mentioned tracking strategy, the straight-line path and the curve path are used as the reference path in the Simulink simulation environment. The results show that the proposed adaptive LOS guidance strategy can make the tracking vehicle's lateral and heading errors converge to zero rapidly, which verifies that the adaptive LOS guidance algorithm can improve the response speed and stability of unmanned vehicle path tracking.