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Adaptive Sliding Mode Path Tracking Control of Unmanned Rice Transplanter

Author

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  • Jinyang Li

    (College of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, Zhenjiang 212013, China)

  • Zhijian Shang

    (College of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, Zhenjiang 212013, China)

  • Runfeng Li

    (College of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, Zhenjiang 212013, China)

  • Bingbo Cui

    (College of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, Zhenjiang 212013, China)

Abstract

To decrease the impact of uncertainty disturbance such as sideslip from the field environment on the path tracking control accuracy of an unmanned rice transplanter, a path tracking method for an autonomous rice transplanter based on an adaptive sliding mode variable structure control was proposed. A radial basis function (RBF) neural network, which can precisely approximate arbitrary nonlinear function, was used for parameter auto-tuning on-line. The sliding surface was built by a combination of parameter auto-tuning and the power approach law, and thereafter an adaptive sliding controller was designed. Based on theoretical and simulation analysis, the performance of the proposed method was evaluated by field tests. After the appropriate hardware modification, the high-speed transplanter FLW 2ZG-6DM was adapted as a test platform in this study. The contribution of this study is providing an adaptive sliding mode path tracking control strategy in the face of the uncertainty influenced by the changeable slippery paddy soil environment in the actual operation process of the unmanned transplanter. The experimental results demonstrated that: compared to traditional sliding control methods, the maximum lateral deviation was degraded from 17.5 cm to 9.3 cm and the average of absolute lateral deviation was degraded from 9.1 cm to 3.2 cm. The maximum heading deviation was dropped from 46.7° to 3.1°, and the average absolute heading deviation from 10.7° to 1.3°. The proposed control method not only alleviated the system chattering caused by uncertain terms and environmental interference but also improved the path tracking performance of the autonomous rice transplanter. The results show that the designed control system provided good stability and reliability under the actual rice field conditions.

Suggested Citation

  • Jinyang Li & Zhijian Shang & Runfeng Li & Bingbo Cui, 2022. "Adaptive Sliding Mode Path Tracking Control of Unmanned Rice Transplanter," Agriculture, MDPI, vol. 12(8), pages 1-14, August.
  • Handle: RePEc:gam:jagris:v:12:y:2022:i:8:p:1225-:d:888196
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    Citations

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    Cited by:

    1. Wenming Chen & Lianglong Hu & Gongpu Wang & Jianning Yuan & Guocheng Bao & Haiyang Shen & Wen Wu & Zicheng Yin, 2023. "Design of 4UM-120D Electric Leafy Vegetable Harvester Cutter Height off the Ground Automatic Control System Based on Incremental PID," Agriculture, MDPI, vol. 13(4), pages 1-18, April.
    2. Jinyang Li & Miao Zhang & Gong Zhang & Deqiang Ge & Meiqing Li, 2023. "Real-Time Monitoring System of Seedling Amount in Seedling Box Based on Machine Vision," Agriculture, MDPI, vol. 13(2), pages 1-26, February.
    3. Wenming Chen & Gongpu Wang & Lianglong Hu & Jianning Yuan & Wen Wu & Guocheng Bao & Zicheng Yin, 2022. "PID-Based Design of Automatic Control System for a Travel Speed of the 4UM-120D Electric Leafy Vegetable Harvester," Sustainability, MDPI, vol. 14(21), pages 1-14, October.
    4. Gongpu Wang & Wenming Chen & Xinhua Wei & Lianglong Hu & Jiwen Peng & Jianning Yuan & Guocheng Bao & Yemeng Wang & Haiyang Shen, 2023. "Design and Simulation Test of the Control System for the Automatic Unloading and Replenishment of Baskets of the 4UM-120D Electric Leafy Vegetable Harvester," Sustainability, MDPI, vol. 15(18), pages 1-19, September.

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