Título: STATE ESTIMATION IN ALCOHOLIC CONTINUOUS FERMENTATION OF ZYMOMONAS MOBILIS USING RECURSIVE BAYESIAN FILTERING: A SIMULATION APPROACH
Autores: Quintero Montoya, Olga Lucia
Amicarelli, Adriana
di Sciascio, Fernando
Scaglia, Gustavo
Fecha: 2008-02-10
Publicador: Bioresources
Fuente:
Tipo: info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Tema: Recursive Bayesian Filtering, State estimation, Biotechnological process, Monte Carlo techniques, Modelling, Simulation
Descripción: This work presents a state estimator for a continuous bioprocess. To this aim, the Non Linear Filtering theory based on the recursive application of Bayes rule and Monte Carlo techniques is used. Recursive Bayesian Filters Sampling Importance Resampling (SIR) is employed, including different kinds of resampling. Generally, bio-processes have strong non-linear and non-Gaussian characteristics, and this tool becomes attractive. The estimator behavior and performance are illustrated with the continuous process of alcoholic fermentation of Zymomonas mobilis. Not too many applications with this tool have been reported in the biotechnological area.
Idioma: Inglés

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