拖拉机作业机组路径跟踪控制方法研究进展

doi:10.16819/j.1001-7216.2025.250104

摘要/Abstract

摘要：

拖拉机作业机组是指由拖拉机与配套机具组成的一种具有独特铰接牵引式结构的农业机械系统，路径跟踪控制方法是实现该机组无人化作业的关键技术。然而，受限于农业环境的多变性及铰接式车体复杂的转向结构，现有方法在适应性、鲁棒性和控制效率方面仍面临挑战。本文旨在通过分析机组模型、路径跟踪控制算法，系统概述拖拉机作业机组路径跟踪控制方法的研究现状。此外，讨论了拖拉机作业机组路径跟踪控制方法研究面临的主要问题及解决思路，以期为拖拉机作业机组路径跟踪控制方法的研究工作提供有益参考。

关键词: 农业机械, 拖拉机, 作业机组, 路径跟踪

Abstract:

The tractor operating unit refers to an agricultural machinery system with a unique articulated tractor structure composed of a tractor and supporting implements, and the path tracking control method is the key technology to realize the unmanned operation of this unit. However, limited by the variability of the agricultural environment and the complex steering structure of the articulated frame, the existing methods still face challenges in terms of adaptability, robustness, and control efficiency. The aim of this work is to provide a systematic overview of current research status on path tracking control methods for tractor operating units by analyzing their models and path tracking control algorithms. In addition, this review discusses the main problems in research on path tracking control methods for tractor operating units and possible solutions, with a view to providing useful references for related research in this field.

Key words: agricultural machinery, tractor, operating unit, path tracking

肖茂华, 田丰瑜, 魏文波, 朱烨均, 李东方, 张鹏程, 耿国盛. 拖拉机作业机组路径跟踪控制方法研究进展[J]. 中国水稻科学, 2025, 39(4): 423-439.

XIAO Maohua, TIAN Fengyu, WEI Wenbo, ZHU Yejun, LI Dongfang, ZHANG Pengcheng, GENG Guosheng. Research on Path Tracking Control Methods for Tractor Operating Units: A Review[J]. Chinese Journal OF Rice Science, 2025, 39(4): 423-439.

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模型 Model	研究内容 Research content	精确性 Accuracy	计算成本 Computational cost	相关文献 Reference
几何学模型 Geometric model	几何特性 Geometric characteristics	低Low	低Low	[15]
运动学模型 Kinematic model	运动特性 Kinematic characteristics	中Medium	中Medium	[16]
动力学模型 Dynamic model	转向特性、稳定特性、振动特性、负载特性 Steering, stability, vibration, and load characteristics	高High	高High	[17-19]

模型 Model	研究内容 Research content	精确性 Accuracy	计算成本 Computational cost	相关文献 Reference
几何学模型 Geometric model	几何特性 Geometric characteristics	低Low	低Low	[15]
运动学模型 Kinematic model	运动特性 Kinematic characteristics	中Medium	中Medium	[16]
动力学模型 Dynamic model	转向特性、稳定特性、振动特性、负载特性 Steering, stability, vibration, and load characteristics	高High	高High	[17-19]

分类 Category	方法 Method	优点 Advantage	缺点 Disadvantag	相关文献 Reference
直接测量法 Direct measurement method	光电传感器 Photoelectric sensor	精度高，可实现直接测量 High accuracy, direct measurement	成本较高，不适用于量产车辆 High cost, not suitable for mass-produced vehicles	[24]
基于模型观察器的估计方法 Model observer-based estimation method	卡尔曼滤波法 Kalman filter method	可直接利用输入进行估计，模型简单，计算效率高 Can directly use inputs for estimation, simple model, high computational Efficiency	精度有限，难以应对复杂和极端工况 Limited accuracy, difficult to handle complex and extreme conditions	[25-28]
	GNSS辅助卡尔曼滤波法 GNSS-assisted Kalman filtering	成本低、估计精度高 Low cost, high estimation accuracy	信号传输易受遮挡物影响，测量速率较低 Signal transmission susceptible to obstructions, low measurement rate	[29,30]
	龙伯格观测器 Luenberger observer	结构简单，易于实现 Simple structure, easy to implement	性能高度依赖于系统模型的准确性 Performance highly depends on the accuracy of the system model	[31]
基于神经网络的估计方法 Neural network-based estimation method	人工神经网络 Artificial neural network	降低了对模型及其相关复杂参数集的依赖 Reduces dependence on the model and complex parameter sets	依赖于训练数据的质量，需要较高的计算资源和时间 Relies on the quality of training data, requires high computational resources and time	[32,33]

分类 Category	方法 Method	优点 Advantage	缺点 Disadvantag	相关文献 Reference
直接测量法 Direct measurement method	光电传感器 Photoelectric sensor	精度高，可实现直接测量 High accuracy, direct measurement	成本较高，不适用于量产车辆 High cost, not suitable for mass-produced vehicles	[24]
基于模型观察器的估计方法 Model observer-based estimation method	卡尔曼滤波法 Kalman filter method	可直接利用输入进行估计，模型简单，计算效率高 Can directly use inputs for estimation, simple model, high computational Efficiency	精度有限，难以应对复杂和极端工况 Limited accuracy, difficult to handle complex and extreme conditions	[25-28]
	GNSS辅助卡尔曼滤波法 GNSS-assisted Kalman filtering	成本低、估计精度高 Low cost, high estimation accuracy	信号传输易受遮挡物影响，测量速率较低 Signal transmission susceptible to obstructions, low measurement rate	[29,30]
	龙伯格观测器 Luenberger observer	结构简单，易于实现 Simple structure, easy to implement	性能高度依赖于系统模型的准确性 Performance highly depends on the accuracy of the system model	[31]
基于神经网络的估计方法 Neural network-based estimation method	人工神经网络 Artificial neural network	降低了对模型及其相关复杂参数集的依赖 Reduces dependence on the model and complex parameter sets	依赖于训练数据的质量，需要较高的计算资源和时间 Relies on the quality of training data, requires high computational resources and time	[32,33]

轮胎模型 Tire model		特点 Characteristics	相关文献Reference
线性轮胎模型 Linear tire model		假设轮胎横向力与侧滑角成正比 Assumes that lateral tire force is proportional to the slip angle	[41]
非线性轮胎模型 Nonlinear tire model	魔术公式轮胎模型 Magic formula tire model	采用一组经验公式来描述轮胎特性，适用于高速、急转弯、滑移等工况 Uses a set of empirical formulas to describe tire characteristics, suitable for high-speed, sharp turns, and sliding conditions	[42,43]
	S形轮胎模型 S-shaped tire model	使用逻辑S形函数或类似函数来描述横向力与侧滑角之间的关系 Uses logical S-shaped or similar functions to describe the relationship between lateral force and slip angle	[44]
	LuGre轮胎模型 LuGre tire model	通过模拟轮胎与路面之间的摩擦行为来计算轮胎的横向力和纵向力，广泛应用于高级车辆动力学仿真 Calculates lateral and longitudinal tire forces by simulating friction behavior between tire and road, widely used in advanced vehicle dynamics simulation	[45-47]
	Burckhardt轮胎模型 Burckhardt tire model	适用于开发和测试针对冬季低摩擦路面条件的车辆控制系统 Suitable for the development and testing of vehicle control systems for winter low-friction road conditions	[48]
	Gim轮胎模型 Gim tire model	适用于描述不同路面条件下轮胎的统一响应 Focuses on the unified description of tire mechanical response under different road conditions	[49]