An optimal control strategy for crop growth in advanced life support systems.

A feedback control method for regulating crop growth in advanced life support systems is presented. Two models for crop growth are considered, one developed by the agricultural industry and used by the Ames Research Center, and a mechanistic model, termed the Energy Cascade model. Proportional and pointwise-optimal control laws are applied to both models using wheat as the crop and light intensity as the control input. The control is particularly sensitive to errors in measurement of crop dry mass. However, it is shown that the proposed approach is a potentially viable way of controlling crop growth as it compensates for model errors and problems associated with applying the desired control input due to environmental disturbances. Grant numbers: NGT5-50229.