Greenhouse Air Temperature Optimal Fuzzy Controller
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abstract
A new scheme of fuzzy optimal control for the temperature of an Agriculture
Greenhouse is presented. The proposed method is based on the Pontryagin’s Minimum
Principle (PMP) that is used to train an adaptive fuzzy inference system to estimate values
for the optimal co-state variables. This work shows that it is possible to successfully control
a greenhouse by using these techniques. A method is presented to control the greenhouse
air temperature achieving significant energy savings by minimizing a quadratic performance
index selected for the desired operating conditions. This approach allows finding a solution
to the optimal control problem on-line by training the system, which can be used on a closedloop
control strategy. Successful simulations results for the controlled system are presented.
