Real Coded Genetic Algorithm for Optimizing Fuzzy Logic Control of Greenhouse Microclimate

Abstract

The artificial intelligent techniques are proposed for the control of the greenhouse microclimate, and a new real-coded genetic algorithm (RCGA) for optimizing fuzzy logic control (FLC) of greenhouse temperature is developed. Based on the balance of the energy, the model of the temperature in the greenhouse is built. According to the model, Gaussian input membership functions the error and the change-in-error of the temperature of FLC is optimised by RCGA in terms of the root-mean-square error (RMSE) with setpoint and input energy. The good performance control curve line of the greenhouse temperature is obtained using the optimized FLC. Compared with the conventional fuzzy control of greenhouse microclimate, it gives better performance in terms of precision, energy and robustness.