Work

Particle Swarm Optimization-Enhanced Fuzzy Control for Electrical Conductivity Regulation in Integrated Water–Fertilizer Irrigation Systems

Year: 2025

Type: article

Abstract: Traditional water–fertilizer control systems often suffer from poor precision and slow response, limiting precision agriculture development. This study developed an electrical conductivity (EC) control system for water–fertilizer integration using a fuzzy Proportional-Integral-Derivative (PID) controller optimized by particle swarm optimization (PSO) and integrated with IoT technology. MATLAB/Simulink simulations showed the proposed controller achieved the smallest overshoot (7.64–8.15%), with average settling time reduced by 62.48 s and 20.38 s compared to conventional PID and fuzzy PID controllers, respectively (p < 0.001). Field experiments on winter wheat demonstrated a mean absolute EC deviation of 0.01125 ms/cm, with root-mean-square error (RMSE) of 0.0217 ms/cm, indicating high precision under field conditions. The system also maintained soil moisture in the optimal range (19–25%) with high irrigation uniformity (Christiansen’s coefficient Cu = 97.6%). The system maintained soil moisture in the optimal range (19–25%) while supporting stable soil nutrient levels and crop growth parameters. This study provides a validated technical solution for precision EC control while establishing a foundation for future fully integrated water–fertilizer management systems.

Source: Automation

DOI: 10.3390/automation6040076

Authors: Jin Yang, Xue Li, Quan Zheng, Lichao Liu

Institution: Anhui Agricultural University

Language: English

Topic: Engineering and Agricultural Innovations

Subfield: Aquatic Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDGs: Zero hunger, Clean water and sanitation, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,207