A fuzzy identification model and fuzzy logic controller was developed aimin
g the environmental control of an agriculture greenhouse. The fuzzy identif
ication of the process was performed by the analysis of the data collected
either during normal operation, as well in reaction to random generated act
uating signals on the heating, ventilation and CO2 injection systems. A com
parative study has been realized between fuzzy and physical models. Using t
he fuzzy model it was possible to implement an accurate Generalized Predict
ive Control (GPC) strategy in order to regulate the environment and to mini
mize energy consumption. The optimal setpoints were computed by means of ba
lancing the benefits associated with the marketable produce against the cos
ts associated with its production. The calculations use growth, photosynthe
sis and climate models. This work describes the practical development of an
fuzzy controller that memorize the optimal strategy, executed by the GPC,
to regulate the temperature and the CO2 concentration of the greenhouse ins
ide air.