Date of Award

5-2014

Document Type

Thesis

Degree Name

Master of Science (MS)

Legacy Department

Electrical Engineering

Advisor

Groff, Richard E.

Committee Member

Burg , Timothy C.

Committee Member

Harcum , Sarah W.

Abstract

Oxygen transfer rate (OTR) is the most signicant signal for aerobic bioprocess control, since most microbic metabolic activity relies on oxygen consumption. However, accurate estimation of OTR is challenging due to the difficulty of determining uncertain oxygen transfer parameters and system dynamics. This paper presents an adaptive estimator, which incorporates exhaust gas, stir speed and dissolved oxygen measurements, to predict the real-time OTR. The design of this estimator takes into account the headspace dilution effect, off-gas sensor dynamics and uncertain oxygen transfer parameters. Accurate and real-time OTR signal is derived by combining the low latency property of stir speed and dissolved oxygen signals with the high accuracy property of off-gas measurements. Proof of convergence of this adaptive estimator is provided under persistently exciting input constraint. Matlab simulation and E. coli fermentation experiment are provided to demonstrate the validity of the adaptive estimator. Through simulation and fermentation experiment, the estimated real-time OTR is shown to accurately track quick changes of oxygen demand in the culture. Thus, it can be applied to a variety of controls and estimation purposes, such as determining when the culture is in oxidative or overflow metabolism. Other related works on bioreactor fermentation control is also provided. A Kalman filter is developed and implemented for real-time feed rate signal estimation. Problems with OUR calculation is discussed when increased oxygen concentrations in the inlet gas and mass flow control are introduced. Two bioreactor related Matlab GUIs, i.e. fermentation GUI and display graph software, are also introduced in the appendices.

Share

COinS