Parameter Identification of a Fed-Batch Cultivation of S. Cerevisiae using Genetic Algorithms

Authors

  • Maria Angelova
  • Stoyan Tzonkov
  • Tania Pencheva

DOI:

https://doi.org/10.55630/sjc.2010.4.11-18

Keywords:

Genetic Algorithms, Parameter Identification, Fed-Batch Cultivation of S. Cerevisiae

Abstract

Fermentation processes as objects of modelling and high-quality control are characterized with interdependence and time-varying of process variables that lead to non-linear models with a very complex structure. This is why the conventional optimization methods cannot lead to a satisfied solution. As an alternative, genetic algorithms, like the stochastic global optimization method, can be applied to overcome these limitations. The application of genetic algorithms is a precondition for robustness and reaching of a global minimum that makes them eligible and more workable for parameter identification of fermentation models. Different types of genetic algorithms, namely simple, modified and multi-population ones, have been applied and compared for estimation of nonlinear dynamic model parameters of fed-batch cultivation of S. cerevisiae.

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Published

2010-03-31

Issue

Section

Articles