A simulation study on the use of co-state variables as strategic setpoints for tomato greenhouses

Modern greenhouses include a large number of control actuators. Such a situation leads to the question of how to divide the control effort between these actuators. This question can be answered using optimal control theory and more particularly the system co-states. By modifying the value of these co-states the grower can control the greenhouse climate and correct deviations due to imperfect modelling or unexpected weather. This work presents a simulation study of this concept for a greenhouse with a tomato crop. For the specific scenarios investigated, by adjusting the co-state two to five times during the season, it was possible to maintain the yield within 6% of its target value. The control costs were on average 10% higher than the control costs that could be achieved if perfect weather forecasts were available at the beginning of the season.