Reaearch On Intelligent Control System Of Temperature And Humidity In Tomato Greenhouse

As the main method of facility agriculture,solar greenhouse is widely used in my country,and facility tomato is an important vegetable variety that is deeply loved by consumers in solar greenhouse.At present,most of the facility tomato greenhouse environment is based on manual regulation and simple threshold control,which depends on the experience of operators,which is highly subjective and inaccurate in environmental control.In order to better meet the needs of the facility tomato growth environment,the greenhouse environment needs to be precisely regulated.The air temperature and humidity are the key environmental factors of the facility tomato greenhouse.The establishment of an accurate temperature,room and humidity prediction model is the basis for the precise control of the temperature,room and humidity.The parameters of the Elman neural network are optimized by using the particle swarm algorithm,and the PSO-Elman algorithm is used to realize the control of the greenhouse.Accurate prediction of temperature and humidity,based on the establishment of the prediction model,a fuzzy PID-based temperature and humidity control model for facility tomato was established,and an intelligent control system for facility tomato temperature,room and humidity was further developed,which realized the control of facility tomato temperature,room temperature and humidity.Intelligent regulation.The specific research contents and results are as follows:(1)Research on greenhouse temperature and humidity prediction model based on PSO Elman algorithmTaking the temperature and humidity of the facility tomato temperature as the research object,the environment inside and outside the greenhouse is thoroughly perceived through the Internet of Things environmental monitoring system.After screening of impact factors and data preprocessing,a prediction model of temperature,room and humidity based on Elman neural network was established.Comparing Elman neural network with BP neural network,Elman neural network has higher prediction accuracy.In order to enhance the global optimization ability of the network,the particle swarm algorithm was introduced to optimize the parameters of the Elman neural network,so as to avoid the network falling into the local minimum value.Compared with Elman neural network,the prediction accuracy of temperature,room and humidity prediction model based on PSO-Elman algorithm is higher,and the coefficient of determination of temperature and humidity reaches 0.9235 and 0.9227,respectively.(2)Research on temperature and humidity control model of facility tomato temperature based on fuzzy PIDCombined with the optimal temperature and humidity growth conditions of facility tomato,on the basis of the research on the mechanism model of facility tomato temperature and humidity,the regulation strategy of temperature and humidity of facility tomato is researched and formulated,PID controller and fuzzy controller are designed,and fuzzy control and PID control are designed.Combined,a fuzzy PID controller is designed,and the fuzzy PID controller has the fastest response speed,the lowest overshoot and the best control ability through simulation comparison.Combined with the precise management requirements of facility tomato,based on the temperature,room,and humidity prediction model,a temperature,room,and humidity control model for facility tomato was constructed.(3)Design and implementation of intelligent control system for temperature and humidity of facility tomato temperatureCombined with the actual needs of facility tomato temperature and humidity control,based on the Internet of Things architecture,the overall design of the facility tomato temperature,room and humidity intelligent control system is carried out,and the Io T sensing terminal,transmission terminal,and control terminal are designed in detail.Developed the lower computer system,upper computer software and mobile APP mobile terminal,embedded the program script of the facility tomato temperature,room temperature and humidity prediction model and regulation model into the upper computer software,and realized the data visualization,on-site control,remote control and automatic control of the facility tomato greenhouse.The intelligent control of the temperature and humidity of the facility tomato was finally realized.