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Research on Path Tracking of Unmanned Spray Based on Dual Control Strategy

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  • Haojun Wen

    (College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
    Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832000, China)

  • Xiaodong Ma

    (College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China)

  • Chenjian Qin

    (College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China)

  • Hao Chen

    (College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China)

  • Huanyu Kang

    (College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China)

Abstract

The high clearance spray is a type of large and efficient agricultural machinery used for plant protection, and path tracking control is the key to ensure the efficient and safe operation of spray. Sliding mode control and other methods are commonly used abroad to track vehicles, while fuzzy control, neural networks and other methods are commonly used at home. However, domestic and foreign research on autonomous agricultural machinery is mainly focused on tractors and other machinery, while research on self-propelled spray in high clearance is less abundant. This paper takes the path tracking algorithm in the integrated navigation system of spray as the main research goal, studies the path tracking control algorithm for straight lines and turning curves that can realize the automatic driving of spray by establishing the path tracking algorithm for unmanned spray based on dual control strategies, designs the path tracking controller, including the preview model theoretical path tracking controller and variable domain fuzzy controller, and determines the preview model through the design of the preview model theoretical path tracking controller. The lateral and longitudinal errors of the model algorithm are analyzed, and the driving characteristics under the complex spray road surface are analyzed. The design of the variable domain fuzzy predictor theory path tracking controller is proposed, and the design of the road model selection controller is calculated and analyzed in detail, including the determination of the road roughness coefficient and the selection of the range of the difference between the average value of the excitation before and after sampling, which improves the performance of the spray path tracking algorithm. The experiment shows that the proposed path tracking control algorithm can meet the path tracking requirements of unmanned spray in the current road environment, and provide a reliable solution for the automatic control of high clearance spray.

Suggested Citation

  • Haojun Wen & Xiaodong Ma & Chenjian Qin & Hao Chen & Huanyu Kang, 2024. "Research on Path Tracking of Unmanned Spray Based on Dual Control Strategy," Agriculture, MDPI, vol. 14(4), pages 1-14, April.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:4:p:562-:d:1368618
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    Cited by:

    1. Guannan Lei & Shilong Zhou & Penghui Zhang & Fei Xie & Zihang Gao & Li Shuang & Yanyun Xue & Enjie Fan & Zhenbo Xin, 2025. "Stability Control of the Agricultural Tractor-Trailer System in Saline Alkali Land: A Collaborative Trajectory Planning Approach," Agriculture, MDPI, vol. 15(1), pages 1-19, January.
    2. Huanyu Liu & Zhihang Han & Junwei Bao & Jiahao Luo & Hao Yu & Shuang Wang & Xiangnan Liu, 2025. "Intelligent Path Tracking for Single-Track Agricultural Machinery Based on Variable Universe Fuzzy Control and PSO-SVR Steering Compensation," Agriculture, MDPI, vol. 15(11), pages 1-28, May.
    3. Yu Luo & Dekui Pu & Xiaoli He & Lepeng Song & Simon X. Yang & Weihong Ma & Hanwen Shi, 2025. "Trajectory Tracking Control of an Orchard Robot Based on Improved Integral Sliding Mode Algorithm," Agriculture, MDPI, vol. 15(17), pages 1-33, September.
    4. Bingbo Cui & Xinyu Cui & Xinhua Wei & Yongyun Zhu & Zhen Ma & Yan Zhao & Yufei Liu, 2024. "Design and Testing of a Tractor Automatic Navigation System Based on Dynamic Path Search and a Fuzzy Stanley Model," Agriculture, MDPI, vol. 14(12), pages 1-17, November.

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