Deterministic and stochastic modelling of greenhouse microclimate

In order to improve the yield and quality of greenhouse crops, it is necessary to develop a reliable model to predict and control the microclimate of greenhouse. In this paper, the problem of deterministic and stochastic modelling for greenhouse microclimate defined by the variables of temperature and humidity is considered. Experiments were conducted in a naturally ventilated single-sloped greenhouse without crops in north China. Firstly, a mechanism model is adopted and the assumed unknown parameters are derived by using increased convergence factor particle swarm optimization algorithm. Secondly, considered the disturbance is independent identically distributed white noise, a stochastic dynamic model is constructed and the parameters are obtained by using maximum likelihood estimate. Finally, a comparison of measured and simulated data is given to show that the proposed models can reasonably forecast internal greenhouse microclimate