Research On Greenhouse Temperature Control Strategy And Development Of Automatic Control Platform

Greenhouse production improves resource utilization and crop yield through the integration of a variety of control equipment and technology to achieve high output and high efficiency.In order to solve the problem that the existing greenhouse environment control technology is not mature and relies on personal planting experience,the experimental greenhouse is built based on and integrated with the Internet of Things technology,sensor technology and intelligent control technology.Aiming at the problem of greenhouse temperature control,the experimental research is carried out and the control strategy is designed.The intelligent centralized management platform of greenhouse is integrated to realize the remote monitoring of greenhouse system.The main results are as follows:(1)Based on the principle of set-point control method,the multi-section control strategy and the control strategy based on heat balance are designed in summer and winter respectively.In summer,the mathematical models of temperature and relative humidity changes in greenhouse without equipment operation were established through four kinds of treatment experiments of cooling,dehumidification,humidification and no equipment operation.By comparing the simulation values of no equipment operation with the measured values of equipment regulation and control under the same conditions,the regulation and control ability of different equipment was quantitatively analyzed.A multi-zone temperature and humidity control method is proposed,which divides the time period according to the crop demand and divides the temperature zone according to the equipment control ability;In winter,based on the analysis of greenhouse heat transfer principle,the comprehensive heat transfer coefficient and the performance parameters of the equipment were calculated by the measured data.According to the greenhouse heat balance equation,the mathematical relationship between the control time of the control equipment and the greenhouse environmental parameters was established,and the temperature control strategy was proposed.The real-time environmental data collected by sensors were used as input.And output that required work time of the equipment and controlling the equipment to start and stop according to the working time.(2)Aiming at the research on the optimal control method of greenhouse environment,the dynamic programming algorithm is proposed to solve the problem.A mathematical model including indoor environmental state variables,optimization decision variables and outdoor random variables is established,and the model predictive control is used to solve the cost function with the goal of temperature close to the expected value and lower energy consumption,and the quadratic programming method is used to optimize the state of each moment step by step,and then the control strategy model is obtained by training the relationship between indoor environmental state variables and optimization decision variables.The Python software is used to write the control program,which takes the sensor data as the input,and the control system feeds back the optimal control under the current environment to regulate and control(3)Design and build an automatic control platform for greenhouse.The overall framework of greenhouse intelligent control is designed,which is composed of field monitoring subsystem,remote monitoring subsystem and cloud box of Internet of Things,and the hardware composition and connection mode of field monitoring subsystem are defined,and the software and hardware design are completed.The engineering configuration of the cloud box system of the Internet of Things is used to realize the local-remote synchronization of data.The functions of each part of the remote monitoring subsystem are defined,and the greenhouse centralized management platform is designed and developed by using cloud configuration software.At the same time,the human-computer interaction interface for mobile phone We Chat applet is designed to realize the remote monitoring of the greenhouse system.