Abstract: The path tracking accuracy of intelligent agricultural machinery is affected by many factors such as field terrain and machinery structure, which may lead to serious consequences such as crushing the drip irrigation belt. In this paper, taking the cotton planter as the research object, a switching tracking algorithm consisting of Stanley tracking algorithm and linear quadratic optimal control (LQR) algorithm is proposed to guide the agricultural machine to enter the line quickly and maintain the straight line accuracy. In addition, in order to eliminate the static lateral error, an extended Kalman filter (EKF) for heading angle error is added. The simulation results show that the switching tracking algorithm can eliminate the static lateral error after entering the straight target line. The real vehicle test results show that when the given initial lateral error is 0.5 m and the speed is 3.6 km/h, the entry time is 6.88 s, and the overshoot is 0.041 m. When the given initial lateral error is 0 m, and the speed is 3.6 km/h, the straightline tracking accuracy is controlled within ±0.025 m, which meets the requirements of highprecision straightline operation of actual agricultural machinery. It shows that the algorithm studied has good tracking accuracy and antiinterference ability and it is conducive to improving agricultural production efficiency.

Key words: intelligent agricultural machinery, positioning technology, extended Kalman filter, path tracking, automatic driving

摘要： 智能农机的路径跟踪精度受田地地形、农机结构等多因素的影响，会导致压坏滴灌带等严重后果。以棉花播种机为研究对象，提出一种由Stanley跟踪算法和线性二次最优控制(LQR)算法组成的切换式跟踪算法，引导农机快速入线和保持直线精度；另外为消除静态横向误差，加入针对航向角误差的扩展卡尔曼滤波器(EKF)。仿真结果显示，切换式跟踪算法在进入目标直线后可有效消除静态横向误差。实车试验结果表明，当给定初始横向误差为0.5 m，速度为3.6 km/h时，入线时间为6.88 s，超调量为0.041 m；当给定初始横向误差为0 m，速度为3.6 km/h时，直线跟踪精度控制在±0.025 m范围内，满足实际农机高精度的直线作业要求，表明该算法具有良好的跟踪精度和抗干扰能力，有利于提升农业生产效率。

关键词: 智能农机, 定位技术, 扩展卡尔曼滤波, 路径跟踪, 自动驾驶