Optimal Control of Greenhouse Climate using Real-World Weather Data and Evolutionary Algorithms

The use of evolutionary algorithms for calculation of the optimal control of the states of a greenhouse system will be presented. The integrated model employed (greenhouse climate, crop growth, outside weather conditions and control equipment) predicts temperature, air humidity and CO2 concentration in a time interval of 15-60 minutes (short time-scale model). The paper presents the optimization of the control of the greenhouse climate to maximize the profit under certain constraints (for instance, prevention of stress for the crops) using evolutionary algorithms. By incorporation of problem specific knowledge into the evolutionary algorithm better results were produced in a shorter time. The results of optimization for optimal control using real world weather data are shown.