Controlling Microbial Byproducts Using Model-based Substrate Monitoring and Control Strategies 2000-01-2399

A computer-controlled bioreactor system was developed to study various aspects of microbially-mediated nitrogen cycling. The system is used to investigate methods for controlling microbial denitrification (the dissimilatory reduction of nitrate to nitrous oxide and dinitrogen) in hydroponic plant growth chambers. Such chambers are key elements of advanced life support systems being designed for use on long duration space missions, but nitrogen use efficiency in them is significantly reduced by denitrification. Control software architecture was designed which permits the heterogeneous control of system hardware using traditional feedback control, and quantitative and qualitative models of various system features. Model based control entails prediction of future system states and automated regulation of system parameters to achieve desired, and avoid undesirable, system states. A bacterial growth rate model based on the classic Monod model of saturation kinetics was used to evaluate the response of denitrifying species to changes in nitrate and oxygen concentrations. The model was then applied to the growth dynamics of mixed microbial communities harvested from the root zone of a hydroponic growth chamber. The use of this Monod organism interaction model was evaluated as a means of achieving more accurate description of the response of this mixed community to changes in oxygen and nitrate concentrations. A minimum variance parameter estimation routine was also used to calibrate the constant parameters in the model by iterative evaluation of substrate (nitrate) uptake and growth kinetics. This representation of processes and interactions aids in the formulation of control laws. The denitrification control strategy being developed will help reduce nitrate resupply requirements, limit the accumulation of undesirable waste products (NO_x), and improve overall nitrogen use efficiency. We also anticipate that increased system autonomy will support reduced crew intervention time although such analyses are beyond the scope of this research.