Model reduction of aerobic bioprocess models for efficient simulation

Full title: 

Model reduction of aerobic bioprocess models for efficient simulation

Abstract:

Owing to the increasing demand for large scale and high efficiency in manufacturing processes, computer aided tools for process operation and control are rapidly gaining popularity. An important state variable in aerobic processes is the dissolved oxygen, which can be easily measured online and is an important indicator of the metabolic activity. However, due to the fast kinetics of the oxygen transfer, dynamical models describing aerobic bioprocesses tend to be highly stiff. This can lead to significant numerical problems hampering its use for fixed step discretization methods and computationally costly applications such as computer fluid dynamics. In this work we use the slow-motion invariant manifold and the quasi steady state assumption methods to eliminate the differential equation describing the dissolved oxygen (the fast mode). By doing this, the tractability of the model is significantly increased with a neglectable loss in description power. The reduced model is also useful for simplifying the observer design problems, which is demonstrated by a state and parameter estimation example at the end of the work.