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Path Tracking Control of a Large Rear-Wheel–Steered Combine Harvester Using Feedforward PID and Look-Ahead Ackermann Algorithms

Author

Listed:
  • Shaocen Zhang

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Qingshan Liu

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Haihui Xu

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Zhang Yang

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Xinyu Hu

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Qi Song

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Key Laboratory for Theory and Technology of Intelligent Agricultural Machinery and Equipment of Jiangsu University, Zhenjiang 212013, China)

  • Xinhua Wei

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Key Laboratory for Theory and Technology of Intelligent Agricultural Machinery and Equipment of Jiangsu University, Zhenjiang 212013, China)

Abstract

Autonomous driving solutions for agricultural machinery have advanced rapidly; however, large-wheeled harvesters present unique challenges compared to traditional vehicles. Specifically, the 5.4 m cutting width, 9.2 m minimum turning diameter, and rear-wheel–steered configuration demand specialized path tracking and steering methods. To address these challenges, this study developed an integrated system combining feedforward PID and Look-Ahead Ackermann (LAA) algorithms with sensors, actuators, and an embedded control platform. Field experiments indicated that the system maintained an average lateral deviation of approximately 5 cm on straight-line paths, with slightly larger errors observed only during turning or alignment maneuvers. Additionally, a “three-cut” steering method was implemented, which enhanced path tracking accuracy and prevented crop damage at headland turns. Successful field tests confirmed the robustness of the developed system, highlighting its practical potential for production-level autonomous harvesting.

Suggested Citation

  • Shaocen Zhang & Qingshan Liu & Haihui Xu & Zhang Yang & Xinyu Hu & Qi Song & Xinhua Wei, 2025. "Path Tracking Control of a Large Rear-Wheel–Steered Combine Harvester Using Feedforward PID and Look-Ahead Ackermann Algorithms," Agriculture, MDPI, vol. 15(7), pages 1-23, March.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:7:p:676-:d:1617963
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    References listed on IDEAS

    as
    1. Tiantian Jing & Zhong Tang & Zhao Ding & Yaquan Liang & Meng Fang & Ting Wang, 2024. "Paddy Soil Compaction Effect Undergoing Multi-Dimensional Dynamic Load of Combine Harvester Crawler," Agriculture, MDPI, vol. 14(2), pages 1-18, January.
    2. Hamed Etezadi & Sulaymon Eshkabilov, 2024. "A Comprehensive Overview of Control Algorithms, Sensors, Actuators, and Communication Tools of Autonomous All-Terrain Vehicles in Agriculture," Agriculture, MDPI, vol. 14(2), pages 1-42, January.
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