Modeling and identification of the bio-ethanol production process from starch: Cybernetic vs. unstructured modeling

Silvia Ochoa, Ahrim Yoo, Jens U. Repke, Günter Wozny, Dae Ryook Yang

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

In this work, an unstructured and a cybernetic model are proposed and compared for the Simultaneous Saccharification_- Fermentation process from Starch to Ethanol (SSFSE), in order to have good, reliable, and highly predictive models, which can be used in optimization and process control applications. The cybernetic is a novel model, which especially considers i) the starch degradation into both glucose and dextrins, and ii) the dynamic behavior of the concentration of the main enzymes involved in the intracellular processes, giving a more detailed description of the process. Furthermore, a new identification procedure based on a sensitivity index is proposed to identify the best set of parameters that not only minimizes the error function, but also contains a fewer number of parameters depending on the initial conditions of the process. Finally, an application of the two models for controlling the SSFSE process using an NMPC (following an optimal reference trajectory for the ethanol concentration) is presented, showing the potential and usefulness of each type of models.

Original languageEnglish
Title of host publicationComputer Aided Chemical Engineering
Pages707-712
Number of pages6
Volume25
DOIs
Publication statusPublished - 2008 Oct 7

Publication series

NameComputer Aided Chemical Engineering
Volume25
ISSN (Print)15707946

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Keywords

  • Cybernetic Model
  • Ethanol
  • NMPC
  • Parameter Identification
  • Sensitivity Analysis

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

Cite this

Ochoa, S., Yoo, A., Repke, J. U., Wozny, G., & Yang, D. R. (2008). Modeling and identification of the bio-ethanol production process from starch: Cybernetic vs. unstructured modeling. In Computer Aided Chemical Engineering (Vol. 25, pp. 707-712). (Computer Aided Chemical Engineering; Vol. 25). https://doi.org/10.1016/S1570-7946(08)80123-X