Getting the most out of it: Optimal experiments for parameter estimation of microalgae growth models

Type : ACL
Nature : Production scientifique
Au bénéfice du Laboratoire : Oui
Statut de publication : Publié
Année de publication : 2014
Auteurs (5) : MUNOZ-TAMAYO Rafael MARTINON Pierre BOUGARAN Gaël MAIRET Francis BERNARD Olivier
Revue scientifique : Journal of Process Control
Volume : 24
Fascicule : 6
Pages : 991-1001
DOI : 10.1016/j.jprocont.2014.04.021
URL : http://www.sciencedirect.com/science/article/pii/s095915241400122x
Abstract : Mathematical models are expected to play a pivotal role for driving microalgal production towards a profitable process of renewable energy generation. To render models of microalgae growth useful tools for prediction and process optimization, reliable parameters need to be provided. This reliability implies a careful design of experiments that can be exploited for parameter estimation. In this paper, we provide guidelines for the design of experiments with high informative content based on optimal experiment techniques to attain an accurate parameter estimation. We study a real experimental device devoted to evaluate the effect of temperature and light on microalgae growth. On the basis of a mathematical model of the experimental system, the optimal experiment design problem was formulated and solved with both static (constant light and temperature) and dynamic (time varying light and temperature) approaches. Simulation results indicated that the optimal experiment design allows for a more accurate parameter estimation than that provided by the existing experimental protocol. For its efficacy in terms of the maximum likelihood properties and its practical aspects of implementation, the dynamic approach is recommended over the static approach. (C) 2014 Elsevier Ltd. All rights reserved.
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Commentaire : Times Cited: 1 SI Bernard, Olivier/J-1133-2014 Bernard, Olivier/0000-0003-2539-9014 0 1
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Citation :
Munoz-Tamayo R, Martinon P, Bougaran G, Mairet F, Bernard O (2014) Getting the most out of it: Optimal experiments for parameter estimation of microalgae growth models. J Process Contr 24: 991-1001 | doi: 10.1016/j.jprocont.2014.04.021