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Single-Neuron PID UAV Variable Fertilizer Application Control System Based on a Weighted Coefficient Learning Correction

Author

Listed:
  • Dongxu Su

    (College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang 110866, China)

  • Weixiang Yao

    (College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang 110866, China)

  • Fenghua Yu

    (College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang 110866, China
    Liaoning Engineering Research Center for Information Technology in Agriculture, Shenyang 110299, China)

  • Yihan Liu

    (College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang 110866, China)

  • Ziyue Zheng

    (College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang 110866, China)

  • Yulong Wang

    (College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang 110866, China)

  • Tongyu Xu

    (College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang 110866, China
    Liaoning Engineering Research Center for Information Technology in Agriculture, Shenyang 110299, China)

  • Chunling Chen

    (College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang 110866, China
    Liaoning Engineering Research Center for Information Technology in Agriculture, Shenyang 110299, China)

Abstract

Agricultural unmanned aerial vehicles (UAVs), which are a new type of fertilizer application technology, have been rapidly developed internationally. This study combines the agronomic characteristics of rice fertilization with weighted coefficient learning-modified single-neuron adaptive proportional–integral–differential (PID) control technology to study and design an aerial real-time variable fertilizer application control system that is suitable for rice field operations in northern China. The nitrogen deficiency at the target plot is obtained from a map based on a fertilizer prescription map, and the amount of fertilizer is calculated by a variable fertilizer application algorithm. The advantages and disadvantages of the two control algorithms are analyzed by a MATLAB simulation in an indoor test, which is integrated into the spreading system to test the effect of actual spreading. A three-factor, three-level orthogonal test of fertilizer-spreading performance is designed for an outdoor test, and the coefficient of variation of particle distribution Cv (a) as well as the relative error of fertilizer application λ (b) are the evaluation indices. The spreading performance of the spreading system is the best and can effectively achieve accurate variable fertilizer application when the baffle opening is 4%, spreading disc speed is 600 r/min, and flight height is 2 m, with a and b of evaluation indexes of 11.98% and 7.02%, respectively. The control error of the spreading volume is 7.30%, and the monitoring error of the speed measurement module is less than 30 r/min. The results show that the centrifugal variable fertilizer spreader improves the uniformity of fertilizer spreading and the accuracy of fertilizer application, which enhances the spreading performance of the centrifugal variable fertilizer spreader.

Suggested Citation

  • Dongxu Su & Weixiang Yao & Fenghua Yu & Yihan Liu & Ziyue Zheng & Yulong Wang & Tongyu Xu & Chunling Chen, 2022. "Single-Neuron PID UAV Variable Fertilizer Application Control System Based on a Weighted Coefficient Learning Correction," Agriculture, MDPI, vol. 12(7), pages 1-22, July.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:7:p:1019-:d:862171
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    References listed on IDEAS

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    1. Egidijus Šarauskis & Marius Kazlauskas & Vilma Naujokienė & Indrė Bručienė & Dainius Steponavičius & Kęstutis Romaneckas & Algirdas Jasinskas, 2022. "Variable Rate Seeding in Precision Agriculture: Recent Advances and Future Perspectives," Agriculture, MDPI, vol. 12(2), pages 1-24, February.
    2. Xiantao Zha & Guozhong Zhang & Yuhang Han & Abouelnadar Elsayed Salem & Jianwei Fu & Yong Zhou, 2021. "Structural Optimization and Performance Evaluation of Blocking Wheel-Type Screw Fertilizer Distributor," Agriculture, MDPI, vol. 11(3), pages 1-17, March.
    3. Robert Finger & Scott M. Swinton & Nadja El Benni & Achim Walter, 2019. "Precision Farming at the Nexus of Agricultural Production and the Environment," Annual Review of Resource Economics, Annual Reviews, vol. 11(1), pages 313-335, October.
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    Cited by:

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    2. Zongru Liu & Jiyu Li, 2023. "Application of Unmanned Aerial Vehicles in Precision Agriculture," Agriculture, MDPI, vol. 13(7), pages 1-4, July.

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