ABSTRACT
The dissolved oxygen (DO) is an important variable in aerobic fermentations and affects the cell growth and product formation. Dissolved oxygen control is difficult in batch fermentations because of the time-varying conditions, time delays, and the probe dynamics. Modeling of the various patterns of biological activity in fermentations and their impact on the DO process dynamics is essential to both achieve a satisfactory control and to track the aforementioned patterns. An adaptive pole placement algorithm with time-delay compensation was used for controlling the DO, coupled with system identification using recursively estimated autoregressive models with exogeneous inputs (ARX). The flow rate of O2 in a constant flow rate gas inlet mixture is used as the manipulated variable. Supervision and coordination techniques are applied to improve the control performance. The control performance is affected by the accuracy of the model prediction and the selected time delay. The effect of DO level on the productivity of beta-lactamase using Bacillus subtilis under oxygen-limited conditions is investigated. Beta-lactamase stability is improved under prolonged growth conditions with low DO levels.
