Study On Dynamic Modelling And Control Strategy In Greenhouse Climate System

Greenhouse is an important facility with a high quality and high production of crops. By overcoming the influence of abominable weathers, the greenhouse climate system will get better agricultural productivity and more income for farmers in unit area. The control of greenhouse microclimate is one of the key techniques in modern greenhouse and becoming increasing important. Although the foreign and domestic researchers have done a large amount of work in this field, the controlling system of greenhouse microclimate is still complicated in the areas such as non-linearity and larger time constant and many disturbance variables and strongly coupling and imprecision and uncertainty. The greenhouse microclimate control has been viewed as "a never ending challenge", which has an important theoretical and practical value in promoting the process of agricultural modernization.For meeting the objective of "Research on the Key Technology of Green Agriculture Environmental Control Facilities and Industrial Demonstration (No.2008BADA6B01)", which is one of the key projects in "Eleventh Five-Year" National Science and Technology Support Program, an accurate thermal model for greenhouse microclimate was constructed based on the actual demand of agricultural production and the climate characteristics of North China. And the strategy of climate control in greenhouse were also studied in this project. Main research contents are listed as follows:(1) The simulation model for thermal environment in solar greenhouse was set up, in which the solar radiation, heat radiation, convection and conduction, ventilation and water phase transformation were considered. And the influence on greenhouse microclimate was analyzed. According to thermal law of conservation of energy and heat transfer rule, a group of differential equations on the energy balance of cover, energy balance of inside air, energy balance of north wall, soil, north roof and energy balance of crop were established. And the latent heat of water was considered in each energy balance equation. The simulation results were compared with actual system measurements and the model was validated. So modeling support was provided for environmental control and management.(2) An identification method based on adaptive neural fuzzy inference system (ANFIS) is provided to set up the greenhouse climate model. The parameters of the models were corrected with the experimental data and they might converge to some determined value. The temperature, humidity, light within the greenhouse was predicted applying the models in different seasons, then the forecast value and actual value has a good fitting relationship. The simulation results show that ANFIS is very effective to identify the nonlinear greenhouse climate system and its accurate is very high.(3)A method for temperature control based on FLMBPC is proposed. The greenhouse is treated as a nonlinear SISO process and subjected to strong external disturbances. The approach transforms an optimization problem for a nonlinear greenhouse subject to constrains into a new optimization problem for a linear greenhouse climate system subject to nonlinear constrains in the new input. On this basis, the application of MBPC in the greenhouse system keeps the inside temperature changes in the specified range. The simulation results of FLMBPC compared with that of NLMBPC, show the advantage of feedback linearization combining with model predictive control.(4) In order to solve the energy saving problem of greenhouse climate system, a model predictive control was proposed, which takes the consumption of energy in greenhouse as the objective function. The greenhouse nonlinear model involving control inputs such as heating, ventilation and fog was rebuilt in part of principle, which served as predictive model to predict the instant output. The PSO was used in MPC to solve difficult optimization. The simulation results show the effectiveness of this proposed method.(5) Since the current greenhouse groups are mainly located in remote suburban areas, which results in the inconvenience of greenhouse research and management, the remote monitoring control system for greenhouse environment was developed, wireless sensor network (WSN) based on ZigBee and embedded technology was applied in collecting data from a remote agricultural site, sending it to information gather node through the WSN nodes, preliminary processing it at Information aggregation nodes, and sending it to the server via GPRS module, finally realizing storage, management and analysis in program. Thus the greenhouse groups would be monitored and managed in remote.