|Author: ||I. Seginer|
Traditionally, greenhouse environment controllers were required to maintain as accurately as possible pre-set setpoints.
A new generation of control schemes are now emerging where the setpoints themselves are continuously changed according to internal rules, which utilize some kind of a crop model.
The setpoints are selected to optimize the growth of the crop in view of a certain performance criterion, which usually is the net income.
The various control schemes which were described in the literature may be divided into 4 classes, according to whether they use explicit crop models and or require information about the future for each decision.
The control schemes can be described with the terminology of Pontryagin's maximum principle.
The future greenhouse controller is likely to contain an interpolating algorithm, such as a neural-net, which was previously trained with optimal solutions of likely scenarios.
The role of the grower could be limited to supplying the proper crop, weather and expected price input.
Alternatively, the controller could have bias dials with which the grower would be able to affect the rate of development of selected characteristics of the crop.
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