Optimizing Greenhouse Climate Control: Enhanced Temperature and Humidity Regulation through Self-Tuned Fuzzy PID (ST-FPID) Controller

Abstract

Greenhouse climate control is crucial for optimizing agricultural productivity and energy efficiency. This study investigates the performance of Self-Tuned Fuzzy PID (ST-FPID) controllers compared to conventional PID controllers in regulating temperature and humidity within greenhouse environments. Through extensive simulations, the ST-FPID controller demonstrated superior performance, achieving faster settling times, minimal overshoot, and reduced steady-state errors under varying disturbance conditions. For temperature control, the ST-FPID achieved the setpoint of 21°C within 2 seconds without overshoot, whereas the PID controller required 6 seconds and exhibited a 2.5°C overshoot. In humidity regulation, the ST-FPID reached the setpoint of 60% within 2 seconds, outperforming the PID controller which overshot to 65% before stabilizing. The ST-FPID controller also maintained lower Integral Average Error (IAE) values across all disturbance levels, highlighting its robustness and adaptability. These findings align with prior research advocating for fuzzy logic-based control systems to enhance climate control precision and stability in dynamic agricultural environments. This study validates the practical application of ST-FPID controllers in optimizing greenhouse climate conditions, contributing to improved crop yields and energy efficiency. Future research should focus on further optimizing these adaptive control strategies to enhance their effectiveness amidst increasingly dynamic environmental changes.