Simultaneous real-time estimation of maximum substrate uptake capacity and yield coefficient in induced microbial cultures
Don Fabian Müller, Daniel Wibbing, Christoph Herwig, Julian Kager
Abstract
In this work we present a soft sensor to accurately estimate the yield coefficient YX/S and the substrate uptake capacity qSmax in a cultivation process using offgas measurements and a nonlinear state observer with an underlying mechanistic model. The structural observability analysis of the mechanistic model showed that both parameters are observable given the available measurement information. In different simulation scenarios we analyzed under which conditions an accurate estimation is possible when measurements are uncertain. Testing the proposed soft sensor in-silico showed that qSmax and YX/S can be estimated with reasonable accuracy depending on the parameter sensitivity. Verification of the developed state and parameter estimation was carried out in induced Escherichia coli cultivations. Besides accurate prediction of living biomass, and substrate accumulation, decreasing YX/S and qSmax could be detected. Therefore, the developed soft sensor can be used to control induced cultures and to prevent overfeeding situations.