Kinetic modeling and parameter estimation in a tower bioreactor for bioethanol production

Applied Biochemistry and Biotechnology
Elmer Ccopa RiveraRubens Maciel Filho

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.

References

Jan 1, 1997·Medical & Biological Engineering & Computing·L J ParkT Lee
Apr 20, 2002·Applied Biochemistry and Biotechnology·D I AtalaF Maugeri
Aug 19, 2006·Applied Biochemistry and Biotechnology·Elmer Ccopa RiveraRubens Maciel Filho
Feb 1, 1987·Biotechnology and Bioengineering·A DouradoY Sevely

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