Design and Experimental Verification of an Automatic EC–pH Compensation Algorithm

Le résumé fourni par la source

In response to the global food crisis driven by climate change and urbanization, vertical farming has emerged as a promising solution for stable year-round crop production. However, excessive discharge of nutrient solution and the limitations of manual EC and pH control hinder recycling efficiency and crop growth stability. This study addresses these challenges by designing a fuzzy control algorithm that automatically detects and adjusts EC and pH in real time based on sensor data. The proposed system calculates errors and their rates of change to regulate the injection of diluents and acids/bases through fuzzy inference, minimizing interference between control variables. Experimental validation in a small-scale vertical farm showed that EC and pH stabilized to their target values within approximately 90 and 140 seconds, respectively, with mean errors maintained at ±0.03 and ±0.04. Compared to manual control, total stabilization time was reduced by about 40%, and the average error rate improved by over 52%. This research presents a technical foundation for automatically adjusting discharged nutrient solutions to crop-appropriate quality levels and highlights the need for future work in sensor accuracy enhancement, system scalability, digital twin-based verification, and intelligent control frameworks.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.