Abstract
Maintaining stable temperature and relative humidity (RH) is essential for edible fungi cultivation, yet indoor climates exhibit nonlinear, coupled thermal–moisture dynamics that can degrade disturbance rejection and increase energy use. This study proposes a reproducible lumped-parameter temperature–humidity model and evaluates a dual-loop (SISO × 2) fuzzy-PID regulation strategy in MATLAB/Simulink under standardized simulation scenarios. The model formulates energy and moisture conservation using physically interpretable parameters (air mass, ventilation exchange, heat transfer, and actuator limits), with RH obtained from a psychrometric transformation of humidity ratio. Three benchmark tests are designed for repeatable assessment: set-point tracking, step disturbances (±2 °C and ±5% RH), and periodic disturbances. A Simulated Growth Indicator (SGI) is introduced as a phenomenological model representing potential growth trends under controlled temperature and humidity, rather than actual measured crop yield. The fuzzy-PID strategy is compared with conventional PID and a no-control baseline using unified performance metrics (steady-state deviation, recovery/settling behavior, integral error) and actuator energy consumption computed from explicit power models. Results show that fuzzy-PID achieves faster recovery and lower error accumulation than PID under identical disturbances while reducing total energy consumption (e.g., 5.7 kWh vs. 6.7 kWh in a representative case). Although the plant is dynamically coupled, the controller implementation remains a practical dual-loop structure; the presented framework therefore serves as a reproducible simulation benchmark for controller comparison in high-humidity cultivation stages.