Journal
PROCESS BIOCHEMISTRY
Volume 41, Issue 7, Pages 1682-1687Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.procbio.2006.02.009
Keywords
ethanol fermentation; batch fermentation; parameter estimation; temperature effect; genetic algorithm; quasi-Newton algorithm
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Optimization techniques are evaluated to estimate the kinetic model parameters of batch fermentation process for ethanol production using Saccharomyces cerevisiae. Batch experimental observations at five temperatures (28, 31, 34, 37 and 40 degrees C) are used to formulate the parameter estimation problem. The potential of Quasi-Newton (QN) and Real-Coded Genetic Algorithm (RGA) to solve the estimation problem is considered to find out the optimal solution. Subsequently, the optimized parameters (mu(max) X-max, P-max, Y-x and Y-px) were characterized by correlation functions assuming temperature dependence. The kinetic models optimized by QN and RGA describe satisfactorily the batch fermentation process as demonstrated by the experimental results. (c) 2006 Elsevier Ltd. All rights reserved.
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