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首页> 外文会议>Mediterranean Conference on Control and Automation >Real-Time Look-Ahead Distance Optimization for Smooth and Robust Steering Control of Autonomous Vehicles *
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Real-Time Look-Ahead Distance Optimization for Smooth and Robust Steering Control of Autonomous Vehicles *

机译：自动车辆平稳且强大的转向控制的实时展望远程优化*

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摘要

This paper presents an optimization problem for the look-ahead distance used in lateral automated vehicle control. A relation is formulated to describe the sensitivity of the control input steering speed $dot delta $ with respect to the variation of the look-ahead distance L. The nonlinear relation is written as an LPV model using the grid-based approach. The aim is to design a controller which minimizes the steering speed $dot delta $ by optimizing an additional look-ahead distance Ld that is added to the nominal look-ahead distance. Such action generates a smooth/stable vehicle motion when subjected to high oscillations due to noises, large lateral errors, etc. The proposed solution is based on the Linear Parameter Varying (LPV) control approach, where an output-feedback dynamic controller is designed based on Linear Matrix Inequalities (LMIs). The control synthesis is carried out using the grid-based approach combined with the ${mathcal{H}_infty }$ control problem. Simulation results show the tracking performance and the smoothness of the steering input, when the vehicle is subjected to successive large lateral errors, which provides a comfortable riding.
机译：本文提出了横向自动化车辆控制中使用的远程距离的优化问题。制定了一种关系，以描述控制输入转向速度$ dot delta $关于寻找远程距离L的变化的灵敏度。使用基于网格的方法写入非线性关系作为LPV模型。目的是设计一个控制器，通过优化额外的展望距离L来最大限度地减少转向速度$ dot delta $ l d 添加到名义上前方的距离。由于由于噪声，大横向误差等引起的高振荡，这种动作产生平滑/稳定的车辆运动。所提出的解决方案基于线性参数变化（LPV）控制方法，其中基于输出反馈动态控制器关于线性矩阵不等式（LMI）。使用基于网格的方法与$ { mathcal {h} _ infty} $控制问题相结合进行控制合成。仿真结果表明，当车辆经受连续的大横向误差时，转向输入的跟踪性能和平滑度，这提供了舒适的骑行。

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