Optimal greenhouse control of tomato-seedling crops
This work presents a control strategy for guiding plant growth development under protected climates using optimal control of constrained continuous processes with iterative dynamic programming. The approach uses a dynamic model of a tomato-seedling crop as well as a mathematical model of an experimental greenhouse. It uses simultaneously both models, along with the analysis of operational costs associated with greenhouse actuators and the benefits resulting from obtaining the crop with the desired characteristics at a certain date. Thus, it is possible to establish the control scheme and policy according to the criterion that generates the highest profit margin in the process. The results from numerical simulations and two laboratory experiments show the performance of the proposed methodology for the crop-management system. Crop evolution is represented by means of two state variables, and the optimal control policy is represented by the sequence of two control actions.
optimal control iterative dynamic programming final state constraints state constraints