Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/60977
Type: Artigo de periódico
Title: Kinetic modeling and parameter estimation in a tower bioreactor for bioethanol production
Author: Rivera, EC
da Costa, AC
Lunelli, BH
Maciel, MRW
Maciel, R
Abstract: In this work, a systematic method to support the building of bioprocess models through the use of different optimization techniques is presented. The method was applied to a tower bioreactor for bioethanol production with immobilized cells of Saccharomyces cerevisiae. Specifically, a step-by-step procedure to the estimation problem is proposed. As the first step, the potential of global searching of real-coded genetic algorithm (RGA) was applied for simultaneous estimation of the parameters. Subsequently, the most significant parameters were identified using the Placket-Burman (PB) design. Finally, the quasi-Newton algorithm (QN) was used for optimization of the most significant parameters, near the global optimum region, as the initial values were already determined by the RGA global-searching algorithm. The results have shown that the performance of the estimation procedure applied in a deterministic detailed model to describe the experimental data is improved using the proposed method (RGA-PB-QN) in comparison with a model whose parameters were only optimized by RGA.
Subject: ethanol fermentation
parameter estimation
modeling
optimization techniques
artificial intelligence
Country: EUA
Editor: Humana Press Inc
Rights: fechado
Identifier DOI: 10.1007/s12010-007-8062-6
Date Issue: 2008
Appears in Collections:Unicamp - Artigos e Outros Documentos

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