Research Projects

This project aims to develop model predictive control (MPC) strategies to maximize HA production of the desired grade using Near-infrared spectroscopy-based measurements and constraint-based models. The project combines information from process-level information (extracellular) and intracellular metabolism obtained by genome-scale metabolic models to achieve higher HA titers of a desired grade in the presence of process disturbances and parametric changes. The project aims to apply dynamic flux balance analysis (DFBA) to understand the effect of process-level changes on intracellular metabolism, develop reduced constraint-based metabolic (RCM) models of HA production under different process conditions, formulate an MPC problem to maximize HA productivity, and track setpoint changes in glucose and acetate concentration values for online switching grades of HA. All MPC strategies will be validated through experiments.