论文标题

基于强大的管LPV-MPC用于自动巷道

Robust tube-based LPV-MPC for autonomous lane keeping

论文作者

Nezami, Maryam, Abbas, Hossam Seddik, Nguyen, Ngoc Thinh, Schildbach, Georg

论文摘要

本文提出了一种控制架构,用于自动驾驶汽车。在本文中,车辆动力学由两个部分组成:侧向和纵向动力学。因此,控制体系结构包括两个随后的控制器。纵向模型预测控制(MPC)使车辆轨道轨迹轨道轨道稳定为速度计划者所产生的所需纵向速度。然后将纵向速度传递到侧向MPC进行车道保持。由于横向动力学对纵向速度的依赖性,它们以线性参数变化(LPV)形式表示,其中其调度参数是车辆的纵向速度。为了处理未来纵向速度(调度参数)的不精确信息,围绕未来纵向速度的名义轨迹考虑了不确定性的界限。然后,采用了基于管的LPV-MPC来控制达到车道保持目标的横向动力学。最后,通过进行仿真测试来说明所提出方法的有效性。

This paper proposes a control architecture for autonomous lane keeping by a vehicle. In this paper, the vehicle dynamics consist of two parts: lateral and longitudinal dynamics. Therefore, the control architecture comprises two subsequent controllers. A longitudinal model predictive control (MPC) makes the vehicle track the desired longitudinal speeds that are assumed to be generated by a speed planner. The longitudinal speeds are then passed to a lateral MPC for lane keeping. Due to the dependence of the lateral dynamics on the longitudinal speed, they are represented in a linear parameter-varying (LPV) form, where its scheduling parameter is the longitudinal speed of the vehicle. In order to deal with the imprecise information of the future longitudinal speed (the scheduling parameter), a bound of uncertainty is considered around the nominal trajectory of the future longitudinal velocities. Then, a tube-based LPV- MPC is adopted to control the lateral dynamics for attaining the lane keeping goal. In the end, the effectiveness of the proposed methods is illustrated by carrying out simulation tests.

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