Resumo

LOPEZ-CRUZ, Irineo L.; ROJANO-AGUILAR, Abraham; OJEDA-BUSTAMANTE, Waldo  e  SALAZAR-MORENO, Raquel. Arx models for predicting greenhouse air temperature: a methodology. Agrociencia [online]. 2007, vol.41, n.2, pp.181-192. ISSN 2521-9766.

A procedure is presented for obtaining a dynamic linear model of auto-regression with exogenous variables (ARX) for predicting the behaviour of the air temperature inside a greenhouse. The ARX are dynamic mathematical models derived from the theory of Systems Identification. The input variables of the model were air temperature, solar radiation, wind velocity affecting the ventilation area of the greenhouse and relative humidity, quantified in a meteorological station located 700 m from a greenhouse in Chapingo, State of México. The response variable was the air temperature inside the greenhouse. Samples were taken of the input and output variables of the model every 5 min during a crop cycle. To determine the structure of the best model, as many as 100 000 ARX models were evaluated using the information criteria and final prediction error of Akaike. The adjustment between the simulated and observed temperatures, and the residual analysis, indicated that ARX models of second degree or above, adequately predict the behaviour of the temperature inside the greenhouse.

Palavras-chave : ARX models; black box models; dynamic linear models; greenhouse temperature.

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