Kinetic modeling and parameter estimation in a tower bioreactor for bioethanol production.
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.
Ccopa Rivera
Elmer
E
Laboratory of Optimization, Design and Advanced Control, School of Chemical Engineering, State University of Campinas, P.O. Box 6066, 13081-970, Campinas, SP, Brazil.
da Costa
Aline Carvalho
AC
Lunelli
Betânia Hoss
BH
Maciel
Maria Regina Wolf
MR
Maciel Filho
Rubens
R
D000465:Algorithms; D019149:Bioreactors / Q000382:microbiology*; D018929:Cell Culture Techniques / Q000379:methods*; D003198:Computer Simulation; D000431:Ethanol / Q000378:metabolism*; D007700:Kinetics; D008954:Models, Biological; D010368:Pectins / Q000378:metabolism*; D012441:Saccharomyces cerevisiae / Q000378:metabolism*
D000431:Ethanol; D010368:Pectins