Design and Robustness Analysis of Intelligent Controllers for Commercial Greenhouse

In a commercial greenhouse, variables, such as temperature and humidity, should be controlled with minimal human intervention. A systematically designed climate control system can enhance the yield of commercial greenhouses. This study aims to formulate a nonlinear multivariable transfer function model of the greenhouse model using thermodynamic laws by taking into account the variables that affect the Greenhouse Climate Control System. To control its parameters, Mamdani model-based Fuzzy PID is designed which is compared with the performance of proportional-integral (PI) and proportional-integral-derivative (PID) controllers to achieve a smooth control action. The Fuzzy logic based PID provides robust control actions eliminating the need for conventional tuning methods. The robustness analysis is performed using values obtained from real-time implementation for the greenhouse model for Fuzzy based PID, PI and PID controllers by minimizing the Integral Absolute Error (IAE) and Integral Square Error (ISE). The greenhouse model has strong interactions between its parameters, which are removed by Relative Gain Array (RGA) analysis, thereby providing an effective control strategy for complex greenhouse production. Further, the stability analysis of non-linear greenhouse model is conducted with the help of the bode plot and Nyquist plot. Results show that good control performance can be achieved by tuning the gain parameters of controllers via step responses such as small overshoot, fast settling time, less rise time, and steady-state error. Also, smoother control action was obtained with Fuzzy based PID making the Greenhouse Climate Control System stable.