Résumé
of unknown coefficients in dynamic models. This approach is validated over 4 applications, 2 of which being takenfrom literature: (A) Reproduction of the pharmacokinetic results from [1]: diffusion of a drug between 2 compartments;(B) Reproduction of the fermentation results from [2], non sequential optimal design of 6 fermentationstrials. (C) Order 1 reaction of ascorbic acid in stewed apples; (D) Rice drying, most complex case with no analyticalsolution: optimal use of experimental device to identify unknown heat and mass transfer coefficientsThe objective is to diminish the experimental effort needed to make this identification within acceptable confidenceranges. After each experiment, the next experiment is A-, D- or E-optimally designed. Our design ofexperiments can take into account all experimental constraints and experimental results of al previous experimentsto calculate best experimental conditions and to obtain smallest uncertainties on estimated parameters. In all contexts(A-D), this methodology is applied to a simulated noised experiment, and its stability and convergence isshown to be effective. In the last context (D), this methodology is also applied to a drying pilot plant; the identificationmade with only three real experiments with non-constant drying conditions are shown to be as effective asan identification based on two-factor three-level grid of nine experiments at constant conditions.