Yang et al. (2025) Particle Swarm Optimization-Enhanced Fuzzy Control for Electrical Conductivity Regulation in Integrated Water–Fertilizer Irrigation Systems

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Identification

• Journal: Automation
• Year: 2025
• Date: 2025-11-20
• Authors: Jin Yang, Xue Li, Quan Zheng, Lichao Liu
• DOI: 10.3390/automation6040076

Research Groups

Not specified in the provided text.

Short Summary

This study developed an IoT-integrated, particle swarm optimization (PSO)-optimized fuzzy Proportional-Integral-Derivative (PID) controller for water-fertilizer integration, demonstrating significantly improved electrical conductivity (EC) control precision and response time in both simulations and field experiments on winter wheat.

Objective

• To develop and validate an electrical conductivity (EC) control system for water-fertilizer integration using a fuzzy PID controller optimized by particle swarm optimization (PSO) and integrated with IoT technology, aiming to overcome limitations of traditional systems regarding precision and response time.

Study Configuration

• Spatial Scale: Field experiments on winter wheat plots.
• Temporal Scale: Not explicitly stated, but implies a period sufficient for crop growth monitoring and system response evaluation (e.g., a growing season or a significant portion thereof).

Methodology and Data

• Models used: Fuzzy PID controller, conventional PID controller, Particle Swarm Optimization (PSO) algorithm for controller optimization. Simulations were performed using MATLAB/Simulink.
• Data sources: Simulation results (overshoot, settling time), field experiment measurements (mean absolute EC deviation, root-mean-square error (RMSE) for EC, soil moisture content, irrigation uniformity (Christiansen’s coefficient Cu), soil nutrient levels, crop growth parameters).

Main Results

• Simulations showed the proposed controller achieved the smallest overshoot (7.64–8.15%) and reduced average settling time by 62.48 s compared to conventional PID and by 20.38 s compared to fuzzy PID controllers (p < 0.001).
• Field experiments on winter wheat demonstrated high precision with a mean absolute EC deviation of 0.01125 mS/cm and an RMSE of 0.0217 mS/cm.
• The system maintained soil moisture within the optimal range (19–25%) and achieved high irrigation uniformity (Christiansen’s coefficient Cu = 97.6%).
• Stable soil nutrient levels and positive crop growth parameters were supported by the system.

Contributions

• Provides a validated technical solution for precise electrical conductivity (EC) control in water-fertilizer integration systems, addressing the limitations of poor precision and slow response in traditional systems.
• Establishes a foundation for the development of future fully integrated and intelligent water-fertilizer management systems in precision agriculture.

Funding

Not specified in the provided text.

Citation

@article{Yang2025Particle,
  author = {Yang, Jin and Li, Xue and Zheng, Quan and Liu, Lichao},
  title = {Particle Swarm Optimization-Enhanced Fuzzy Control for Electrical Conductivity Regulation in Integrated Water–Fertilizer Irrigation Systems},
  journal = {Automation},
  year = {2025},
  doi = {10.3390/automation6040076},
  url = {https://doi.org/10.3390/automation6040076}
}