Biomass estimation in batch biotechnological processes by Bayesian Gaussian process regression

• Published in: Computers & chemical engineering Vol. 32; no. 12; pp. 3264 - 3273
• Main Authors: di Sciascio, Fernando, Amicarelli, Adriana N.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 22-12-2008
• Subjects: Bacillus thuringiensis; Bayesian regression; Biomass estimation; Biotechnological process; Extended Kalman filter; Gaussian process; Bayesian regression; Gaussian process; Biotechnological process; Bacillus thuringiensis; Extended Kalman filter; Biomass estimation
• ISSN: 0098-1354; 1873-4375
• DOI: 10.1016/j.compchemeng.2008.05.015

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.