Research On Multi-objective Optimization Control Of Greenhouse Environment Based On Grey Particle Swarm Algorithm

Greenhouse environment control is one of the contents of greenhouse crop production management,which is of great significance for crop quality and yield.It is an important problem that how to control the greenhouse equipment and make the environment parameters in the room to meet the crop growth.In order to reasonably control the greenhouse environment control equipment,to a certain extent,save electricity costs,taking tea seedling greenhouse agriculture Anhui Agriculture University cuiyuan as the research object,through the introduction of artificial control factors,to extend the autoregressive model(Auto Regressive eXogenous,ARX)as the foundation,construction temperature and humidity and economic cost of multi-objective model using function.At last,on the basis of Particle Swarm Optimization(PSO),the gray relational theory is used to carry out multi-objective control for the greenhouse environment.The main contents and results are as follows:(1)According to the spatial characteristics of greenhouse environment,multi-source information collection of tea seedling greenhouse.The information of the temperature and humidity of the greenhouse environment is collected,and then the adaptive weighted fusion estimation algorithm is used to realize the data fusion of multi-source information collected in the greenhouse.With the development of software for the LabVIEW platform to collect indoor environmental information,outdoor environment information collected by using PH automatic weather station,estimation algorithm to preprocess the collected data by wavelet denoising and adaptive weighted fusion,effectively remove noise existed in the process of information collection,to ensure the consistency and reliability of collecting information,prepare for greenhouse environment modeling.(2)Temperature,humidity and energy consumption model of greenhouse environment.Through the introduction of artificial control factors,based on the ARX structure,using the system identification method to identify the structure and parameters of the model,the temperature and humidity of the greenhouse environment model,the accuracy of cross validation to test the temperature and humidity of the model,the simulation results show that the temperature and humidity measured calculation model of temperature and humidity change trend and that ARX model can effectively simulate the temperature and humidity of the greenhouse environment;to consume the electricity in the greenhouse operation control equipment with reference to the establishment of energy cost model.(3)Optimal control of multi objective grey particle swarm optimization algorithm.By introducing the grey relevancy theory,on the basis of the standard PSO algorithm,the control device combination types as the particles in solution,temperature model,humidity model and energy consumption model as objective function,the multi-objective optimization in order to achieve control of greenhouse environment control.The multi-objective grey particle swarm algorithm to optimize the temperature humidity and linear weighted method,single objective particle swarm optimization algorithm are compared with the results of the selection,found this method not only can make the temperature and humidity of the greenhouse environment within the range of crop growth,compared with other two kinds of optimization methods to a certain extent,saving electricity cost.