Research And Implementation Of Temperature And Humidity Intelligent Control Strategy In Greenhouse

Greenhouse is the main place to break through the natural conditions to realize the growth of crops,and it is a very important facility for modern agriculture.The control of greenhouses was focused and two important environmental variables of temperature and humidity were selected as the research objects.The temperature and humidity target value tracking controller was designed,and the forecasting model of the greenhouse was established.At the same time,the temperature and humidity value of the greenhouse based on the accumulated temperature theory Low energy consumption control was established.The specific research content was as follows.According to the mechanism model constructed based on the conservation of heat and energy of the temperature and humidity of the greenhouse,the tracking control of the target value of the temperature and humidity of the greenhouse was realized.In this paper,the real data of the experimental greenhouse and the one-variable regression equation were used to fit the transfer function of the greenhouse temperature and humidity.A genetic algorithm was designed to optimize the quantization factor and correction coefficient of the fuzzy PID temperature and humidity target value tracking controller for this model.The test results showed that the temperature and humidity tracking control rules for the greenhouse designed in this paper can make the controller overshoot.The amount and adjustment time have been reduced,and the control tracking effect has been improved.Based on the support vector regression model,a greenhouse temperature and humidity prediction and identification mode were constructed.The non-linear improvement of the cosine function was used to improve the inertia weight of the particle swarm algorithm to realize the optimization of the support vector regression parameters and identify the greenhouse temperature and humidity prediction model.Combining the characteristics of the accumulated temperature of crops,the intelligent control rules for temperature and humidity were formulated,and the intelligentcontroller for greenhouse accumulated temperature was designed.The predictive control model can reduce the opening time of the actuator and reduce the switching frequency of the control switch,so that the humidity and temperature of the greenhouse can be controlled within suitable environmental conditions for crop growth.Taking the experimental greenhouse of the Intelligent Internet of Things Laboratory of Shenyang University as the test object,the temperature and humidity tracking value controller and the accumulated temperature intelligent controller were actually operated.After testing,the two controllers can operate normally and effectively control the temperature and Humidity.At the same time,it can be used to provide a suitable temperature and humidity environment for the growth and development of lettuce.The two intelligent control strategies designed in this paper,can be realized to provide a suitable temperature and humidity environment for greenhouse production.It can be used to provide the foundation for the subsequent development of more efficient intelligent control decisions and enrich the control methods of greenhouses.It also provided more options for serving agricultural production and life,and contributes scientific and technological strength to targeted poverty alleviation and rural revitalization.