University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Subset selection for improved parameter identification in a bio-ethanol production process

Lopez, D, Barz, T, Arellano-Garcia, H, Wozny, G, Villegas, A and Ochoa, S (2012) Subset selection for improved parameter identification in a bio-ethanol production process Czasopismo Techniczne. Mechanika, 109 (1-M). pp. 137-147.

Text (licence)
Available under License : See the attached licence file.

Download (33kB) | Preview


A systematic approach for system identification is applied to experimental data of ethanol production from cellulose. Special attention is given to the identification of model parameters, which can be reliably estimated from available measurements. For this purpose, an identifiable parameter subset selection algorithm for nonlinear least squares parameter estimation is used. The procedure determines the parameters whose effects are unique and have a strong effect on the predicted (measurement variables) output variables. The system is described by a generic process model for the simultaneous saccharification and fermentation including three enzyme-catalyzed reactions. The process model is clearly over-parameterized. By applying the subset selection approach the parameter space is reduced to a reasonable subset, whose estimated parameters are still able to predict the experimental data accurately.

Item Type: Article
Subjects : Chemical Engineering
Divisions : Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :
Lopez, D
Barz, T
Arellano-Garcia, H
Wozny, G
Villegas, A
Ochoa, S
Date : 2012
Copyright Disclaimer : © 2015 Interdisciplinary Centre for Mathematical and Computational Modelling
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 02 Sep 2016 13:37
Last Modified : 31 Oct 2017 18:39

Actions (login required)

View Item View Item


Downloads per month over past year

Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800