Model-based Compromise Control of Greenhouse Climate using Pareto Optimization

Energy-saving is always in conflict with the control Error-minimizing for real-world engineering application in greenhouse. Moreover, the efficiency of plant production and energy consumption depends largely on the adjustment of greenhouse environment. In order to achieve less energy consumption and higher control precision, this paper presents a kind of compromise control algorithm for Pareto solutions of greenhouse environment control. The models of greenhouse and weather forecast used are described and derived. A series of optimization experiments are presented at any time of a day using Non-dominated Sorting Genetic Algorithm-II(NSGA-II). The results show the feasibility of the proposed method, and it may be valuable and helpful to formulate environmental control strategies, and to achieve high control precision and low energy cost.