Multi-factor Coordination Control Model And Method Of Greenhouse Environment For Benefit-priority

Environment is the key factor that affects the yield and quality of crops in greenhouse.The environmental factors are interrelated,and the control costs are significantly different.For efficient growth of crops,environmental factors need to be controlled.Also,the control cost needs to be considered.Therefore,control method which fulfills the demand of crops and reduces the cost needs to be studied.Based on the analysis of factors affecting the photosynthetic rate of crops,considering the influence of temperature on photosynthetic rate,this paper studied the suitable temperature interval acquisition method using radial basis interpolation-fish swarm algorithm.The establishment method of crop photosynthetic rate prediction model was studied based on genetic support vector machine algorithm,considering the influence of PPFD and CO₂ on photosynthetic rate.Then,the establishment method of the suboptimal photosynthetic rate model based on L discrete curvature-particle swarm optimization algorithm was explored,and the suboptimal target value model of photosynthetic rate was established.Based on the suboptimal photosynthetic rate model and real-time perceptual information,online optimization control method for PPFD and CO₂ concentration was constructed by multi-objective particle swarm optimization algorithm,which was aiming for benefit-priority.Based on the above theoretical researches,the greenhouse environment coordinated control system was designed and carried out for verification.This paper combines the suboptimal photosynthetic rate model and regulation benefits,and proposes a multi-factor coordinated control model for greenhouse environment,which has theoretical significance for the efficient regulation of greenhouse environment and the upgrading of greenhouse industry.The main research contents and conclusions of the thesis are as follows.?1?The interaction mechanism between greenhouse environment and photosynthesis was studied and multi-factor nesting test research was carried out.The suitable photosynthetic temperature interval acquisition method based on radial basis interpolation-two-dimensional fish group optimization algorithm was studied.A photosynthetic rate test scheme for PPFD,temperature and CO₂ nesting was designed to obtain 3,080 test data samples under 14temperature gradients,10 CO₂ gradients and 22 PPFD gradient combinations.The error results of the five kinds of interpolation basis functions test functions showed that the multi-quadratic basis function had the highest precision.The multi-quadratic radial basis interpolation result network was used as the two-dimensional optimal target function of fish swarm algorithm,the two-dimensional optimization of PPFD and CO₂ under different temperature conditions was realized,and the relationship between temperature and photosynthetic rate under PPFD and CO₂ saturation conditions was obtained.Correlation analysis was carried out using the verification test data.The verification results showed that the slope of the fitted line was 1.0070,the intercept was-0.1505,the coefficient of determination was 0.9973,and the root mean square error was 0.5649?mol/?m²?s?.For the optimization results,the L discrete curvature maximum method was used to obtain the suitable temperature interval for photosynthetic of tomato at initial flowering stage,which was[22,32]°C.?2?The acquisition method of suboptimal photosynthetic rate model under temperature constraints was studied.The R² of the genetic algorithm-support vector regression machine photosynthetic rate prediction model was 0.9867,and the RMSE was 1.358?mol/?m²?s?.On this basis,the GA-SVR photosynthetic rate prediction model network was taken as input,and the suitable temperature interval for photosynthetic was taken as the temperature instantiation condition.The curvature of curve on the curved surface was calculated based on the L discrete curvature method.Taking the curvature result as the optimization objective function,the maximum variation of the particle swarm optimization discrete curvature was obtained,and the coordinate point of suboptimal photosynthetic rate was obtained.Finally,based on the LM method,the suboptimal photosynthetic rate function surface was fitted,and the GA-SVR surface instantiated by temperature was intersected to obtain the suboptimal photosynthetic rate model.The result of model calibration showed that the R² between the predicted and measured value of the sub-optimal photosynthetic rate was 0.9843,the slope of the fitted straight line was0.9602,the intercept was 1.344,and the RMSE was 0.3541?mol/?m²?s?.The maximum relative error was less than 3.33%.?3?The PPFD and CO₂ coordinated control target value acquisition method of the benefit-priority greenhouse environment control model was studied,and the benefit analysis was carried out.Taking the suitable temperature,PPFD and CO₂ range as the environmental constraints,the suboptimal photosynthetic rate model as the optimal constrained space,the photosynthetic rate suboptimal target value model and the PPFD and CO₂ total regulation cost function to construct the optimization objective function.MOPSO was carried out with the goal of high photosynthetic rate and low regulation cost,and to obtain the target value of PPFD and CO₂ coordinated control with benefit-priority.The results of the comparative analysis of benefits showed that,the photosynthetic rate of the PPFD and CO₂ coordinated control with benefit-priority decreased by 11.67%on average.However,the average PPFD demand decreased by 36.66%,and the amount of CO₂ required decreased by 29.79%,comparison with the photosynthetic optimal PPFD and CO₂ coordinated regulation methods.Amusing the real-time PPFD in the suitable temperature range was 500?mol/?m²?s?,and the CO₂ concentration was 600?mol/mol.The photosynthetic rate was increased by 22.27?mol/?m²?s?,and the average regulation cost of the coordinated control model with benefit-priority was 0.43 yuan.However,the photosynthetic rate was increased by 26.92?mol/?m²?s?,and the average cost of coordinated control model for optimal photosynthesis was 0.77 yuan.?4?The greenhouse environment coordinate control system was designed and the actual deployment verification was carried out.The system mainly consisted of three parts:sensor monitoring subsystem,data fusion and intelligent decision-making subsystem,and collaborative control subsystem.Among them,the sensor monitoring subsystem mainly realized real-time monitoring and transmission of PPFD,temperature,CO₂,electricity consumption and CO₂ flow in the environment;data fusion and intelligent decision-making subsystem integrated suitable temperature interval acquisition method,suboptimal photosynthetic rate obtaining method,PPFD and CO₂ collaborative control method for benefit priority.When the data were uploaded by the monitoring subsystem,the system determined whether the temperature was in the suitable temperature range.If the temperature range was suitable,the suboptimal photosynthetic rate model of the corresponding temperature was called to perform MOPSO,and the PPFD and CO₂ coordinate control target value for benefit-priority were obtained;If not,it would wait for the next data refresh and then redetermine.The control subsystem drived the corresponding PPFD and CO₂ control equipment according to the target value.The control results were uploaded by the sensor monitoring subsystem,and the closed-loop correction was performed on the control target value.The prototype of the control system was deployed at the Wuquan Experimental Base of the Northwest A&F University.The energy consumption data showed that the average daily consumption cost of the collaborative control system for benefit-priority was 4.46 yuan.The average daily cost of collaborative control system for photosynthetic optimal is 6.76 yuan.Compared with the natural control area,the daily consumption of CO₂ was 1503.17L,and the daily electricity consumption was 2.97KW/h in the collaborative control system for benefit-priority area,the instantaneous photosynthetic rate was increased by 45.15%.The daily consumption of CO₂ was 2290.61L,and the daily electricity consumption was 4.70KW/h in the collaborative control system for photosynthetic optimal area,the instantaneous photosynthetic rate was increased by 53.64%.