Design and Research of Soil Disinfection Pesticide Application Control System Based on PSO-PID Algorithm

Soil-borne diseases and continuous cropping obstacles have become critical factors constraining sustainable agricultural development. Traditional pesticide application methods commonly suffer from uneven dosage distribution, significant chemical waste, and environmental pollution. To enhance the precision and system stability of soil disinfection, this paper designs a precision pesticide application system for soil disinfection based on the Particle Swarm Optimization Proportional-Integral-Derivative algorithm (PSO-PID). Centered on a C37 controller, the system integrates the application pipeline, pumps, electric ball valves, multiple sensors, and a control terminal. The PSO-PID algorithm was deployed on the Codesys V2.3 platform, achieving precise flow control by adjusting electric ball valve openings in conjunction with velocity feedback. Simulink simulations showed that the PSO-PID algorithm outperforms conventional PID control in terms of settling time, overshoot, and steady-state error. Bench tests further validated the effectiveness of the proposed algorithm. Compared to conventional PID, the PSO-PID algorithm demonstrates superior control accuracy, faster response time, and enhanced application stability, with relative errors of 2.33%, 1.25%, and 1.20% respectively, while those of the conventional PID algorithm reach 3.67%, 3.35% and 4.88% respectively, representing a reduction of approximately 50% compared with the conventional PID algorithm. The results of the system application uniformity test indicated that the PSO-PID algorithm reduces relative error by approximately 40% compared to conventional PID, with the coefficients of variation being 2.02%, 1.73% and 1.81% respectively, which represented a significant improvement over those of the conventional PID algorithm (3.36%, 3.13% and 3.81%). Both application uniformity and stability outperform conventional PID algorithms, effectively minimizing application deviation. It outperforms conventional PID in both application uniformity and stability, effectively minimizing application deviation. The findings demonstrate that the proposed PSO-PID application control method achieves high control accuracy and application stability, providing reliable technical support for precision soil disinfection application.

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Publication Details

Journal
Agriculture
Published
2026-02-21
DOI
https://doi.org/10.3390/agriculture16040481
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00

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article

Design and Research of Soil Disinfection Pesticide Application Control System Based on PSO-PID Algorithm

Mengdi Xu, Changyuan Zhai, Zhen Wang, Xiangjie Niu et al.
Agriculture
Smart Agriculture and AI
article

Design and Research of Soil Disinfection Pesticide Application Control System Based on PSO-PID Algorithm

Mengdi Xu, Changyuan Zhai, Zhen Wang, Xiangjie Niu, Zhichong Wang, Wei Zou, Si Li
article en

Abstract

Soil-borne diseases and continuous cropping obstacles have become critical factors constraining sustainable agricultural development. Traditional pesticide application methods commonly suffer from uneven dosage distribution, significant chemical waste, and environmental pollution. To enhance the precision and system stability of soil disinfection, this paper designs a precision pesticide application system for soil disinfection based on the Particle Swarm Optimization Proportional-Integral-Derivative algorithm (PSO-PID). Centered on a C37 controller, the system integrates the application pipeline, pumps, electric ball valves, multiple sensors, and a control terminal. The PSO-PID algorithm was deployed on the Codesys V2.3 platform, achieving precise flow control by adjusting electric ball valve openings in conjunction with velocity feedback. Simulink simulations showed that the PSO-PID algorithm outperforms conventional PID control in terms of settling time, overshoot, and steady-state error. Bench tests further validated the effectiveness of the proposed algorithm. Compared to conventional PID, the PSO-PID algorithm demonstrates superior control accuracy, faster response time, and enhanced application stability, with relative errors of 2.33%, 1.25%, and 1.20% respectively, while those of the conventional PID algorithm reach 3.67%, 3.35% and 4.88% respectively, representing a reduction of approximately 50% compared with the conventional PID algorithm. The results of the system application uniformity test indicated that the PSO-PID algorithm reduces relative error by approximately 40% compared to conventional PID, with the coefficients of variation being 2.02%, 1.73% and 1.81% respectively, which represented a significant improvement over those of the conventional PID algorithm (3.36%, 3.13% and 3.81%). Both application uniformity and stability outperform conventional PID algorithms, effectively minimizing application deviation. It outperforms conventional PID in both application uniformity and stability, effectively minimizing application deviation. The findings demonstrate that the proposed PSO-PID application control method achieves high control accuracy and application stability, providing reliable technical support for precision soil disinfection application.

AgricultureVol. 16(4)
Jiangsu University (CN), Beijing University of Agriculture (CN), Beijing Academy of Agricultural and Forestry Sciences (CN)
National Natural Science Foundation of China, Beijing Academy of Agricultural and Forestry Sciences, National Key Research and Development Program of China
Zero hunger
Openalex Percentile: Top 48%
Smart Agriculture and AI
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