Development of a Fuzzy Logic Controller for Microclimate Regulation under an Agricultural Greenhouse based on a State-Space Model Approach

Abstract

Greenhouse management is a fundamental aspect of modern agriculture, as it directly affects crop quality, water efficiency, and energy consumption. This study focuses on the regulation of key greenhouse climatic parameters, namely indoor temperature and relative humidity. A dynamic greenhouse model was developed to implement and compare two control strategies: a Fuzzy Logic Controller (FLC) and a Proportional–Integral–Derivative (PID) controller. The main objective of this work is to design a controller capable of simultaneously managing two highly correlated variables by adopting variable setpoints for both temperature and humidity. This approach distinguishes the proposed methodology from previous studies, which typically focused on temperature control while maintaining constant humidity setpoints. In contrast, the proposed strategy regulates both parameters dynamically and concurrently. Simulation results under different operating scenarios show that the FLC outperforms the PID controller in maintaining a favorable greenhouse microclimate. In particular, the FLC achieved reductions of 25.1% in average humidification rate and 29.6% in ventilation rate. Moreover, the total energy consumption associated with the PID controller was approximately 27% higher than that of the FLC. The error analysis between reference setpoints and simulated responses confirms that the dynamic model accurately predicts indoor temperature and relative humidity with minimal deviation. Overall, the results demonstrate the robustness and efficiency of the FLC in ensuring optimal greenhouse climatic conditions while significantly reducing energy consumption.