基于几何前馈的自动驾驶叉车自抗扰路径跟踪控制

Longqing Li, K. Song, H. Xie
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引用次数: 0

摘要

自动驾驶叉车作为一项很有前途的技术,可以降低工人的劳动强度,也可以提高物流货物运输的效率。本文提出了一种结合级联自抗扰控制器和基于几何的前馈控制器的路径跟踪控制器。基于运动学模型设计的级联控制器,通过外环减轻期望的航向方向来最小化横向误差,然后通过内环调节转向角度来实现横向误差。将简化的运动学模型与实际叉车运动之间的偏差集中为一个总扰动,由扩展状态观测器(ESO)观察。为了提高系统的瞬态响应,设计了一种基于几何的前馈控制器,通过预瞄计算期望的转向角。该方法有效地提高了响应速度,减小了超调量。实验对算法的有效性进行了定量评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Active Disturbance Rejection Path-following Control for Self- driving Forklift Trucks with Geometry based Feedforward
The self-driving forklift, as a promising technology to reduce the labor intensity of workers, can also improve the efficiency of logistics freight transportation. In this paper, a path-following controller that combines cascaded active disturbance rejection controller and geometry-based feedforward controller, is proposed. The cascaded controller, designed based on a kinematic model, minimizes the lateral error via the outer-loop by mitigating the desired heading direction, and then achieved by the inner loop through adjusting the steering angle. The deviation between the simplified kinematic model and the actual forklift motion is lumped as a total disturbance, to be observed by the extended state observer (ESO). In order to enhance the transient response, a geometry-based feedforward controller is developed, computing the desired steering angle through preview. The proposed method effectively improves the response speed and reduces the overshoot. The effectiveness of the algorithm is quantitatively evaluated in experiments.
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