Biomass estimation in batch biotechnological processes by Bayesian Gaussian process regression

Abstract

This paper proposes a biomass concentration estimator for a batch biotechnological process based on Bayesian regression with Gaussian process. On the basis of experimental data, a two-stage bootstrap technique has been developed for the estimator design. In the first stage, the biomass data set was augmented with virtual filtered measurements, and in the second stage, the biomass estimator design was completed. The method provides information on the confidence level of the estimates, and the biomass estimator performances are illustrated for the Bacillus thuringiensis δ-endotoxins production process.