Design of an Intelligent Greenhouse Remote Control System Based on a Fuzzy Neural Network

There are many changing factors in a greenhouse, and the traditional control method has been unable to obtain a good control effect. In this study, focusing on the fuzzy neural network (FNN), the principles of two control methods and the advantages of their combination were analyzed, an intelligent remote control system for a greenhouse based on the FNN that controls the temperature and humidity was designed, and a simulation experiment was performed in the Simulink environment. The results demonstrated that compared with the traditional proportion, integration, differentiation (PID) control system and the genetic algorithm + fuzzy PID control system, the FNN-based system designed in this study achieved better performance in temperature and humidity control. The temperature error of the FNN-based system was smaller than 1 degrees C, the humidity error was approximately 2%, and the change in the error values was stable. The experimental results verify the reliability of the FNN and provide some theoretical basis for the intelligent control of greenhouses.