A fuzzy logic-based controller for integrated control of protected cultivation

Purpose – The purpose of this paper is to present a fuzzy logic-based control system for controlling the protected cultivation and describes its advantages over the traditional greenhouse automation control systems. Design/methodology/approach – In terms of systems theory, the greenhouse represents a complex non-linear system with emphasized subsystem interactions. Applying a non-linear control encompasses a number of difficulties due to incomplete knowledge of system dynamic. System decoupling is used in order to obtain simplified control structures for independent control loops. This gives limited results due to strong interaction between system variables and such control system does not allow optimization of system behavior primarily in terms of energy efficiency and/or water consumption. Findings – The paper presents a design of fuzzy logic-based controller, which optimizes the greenhouse energy and water consumption. The design includes the main linguistic variables for sensor and actuator subsystems. Membership functions of Fuzzy Inference System (FIS) are generated and simulation and analysis of the behavior of the designed control system is performed. Research limitations/implications – Obtained result shows that the designed control system beside its relative simplicity is flexible and adaptive, taking into account the differences in crop varieties and growth stages. Practical implications – Preliminary simulation of energy savings compared with the costs on actual field shows also good results. Still, number of different control strategies has to be applied in order to increase system flexibility regarding the different varieties and different stages of their growth. Originality/value – Obtaining an integrated controller based on fuzzy logic will highly improve possibilities for mass production of cheap technology. It will be easy to use by growers enabling them to incorporate their own informal growing knowledge and to create actual growing control strategy.