Abstract: Due to the effect of outside meteorological conditions, greenhouse covering materials, greenhouse structure and the growth and variety of greenhouse crops and their cultivation methods, a greenhouse temperature system has the characteristics of large time delay, nonlinearity, strong external noise disturbances, time variance. Parameter modeling can hardly describe model structures online. A method was thus proposed, which uses the finite impulse response(FIR) model to describe the temperature system and identify the time delay through the sparsity of FIR sequences. First, the sparsity of FIR sequences were analyzed. Then, according to the compressed sensing theory, a relatively small amount of data to recover the FIR sequences by solving the sparse optimization problems, hereby obtaining the time delay property of the system. Finally, the parameters of FIR model were identified. The time delay of the outside temperature, outside solar radiation, cooling pad, is 6 minutes, 1 minute and 1 minute, respectively. These results are consistent with the mechanism model of the greenhouse temperature system. As the control equipment is incapable of continuous control, the “on” and “off” status of the equipment was brought into the model which was built under the effect of the Wet Curtain-Fan. The fitting of the model was 9468%, 9414% when the Wet Curtain-Fan was on or off, suggesting that the model has higher credibility.

Key words: greenhouse system identification, FIR model, time delay, sparse optimization, compressed sensing