| Titre : | PCA combined model-based design of experiments (DOE) criteria for differential and algebraic system parameter estimation (2008) |
| Auteurs : | Yang Zhang, Auteur ; Thomas F. Edgar, Auteur |
| Type de document : | Article : texte imprimé |
| Dans : | Industrial & engineering chemistry research (Vol. 47 N°20, Octobre 2008) |
| Article en page(s) : | P. 7772-7783 |
| Note générale : | Chemical engineering |
| Langues : | Anglais |
| Tags : | Design of experiments (DOE) |
| Résumé : | Design of experiments (DOE) for parameter estimation in dynamic systems is receiving more attention from process system engineers. In this paper, a principal component analysis (PCA)-based optimal criterion (P-optimal) for model-based DOE is proposed that combines PCA with information matrix analysis. The P-optimal criterion is a general form that encompasses most widely used optimal design criteria such as D-, E-, and SV-optimal, and it can automatically choose the optimal objective function (criterion) to use for a specific differential and algebraic (DAE) system. Two engineering examples are used to validate the algorithms and assumptions. The advantages of P-optimal DOE include ease of reducing the scale of the optimization process by choosing parameter subsets to increase estimation accuracy of specific parameters and avoid an ill-conditioned information matrix. |
| En ligne : | http://pubs.acs.org/doi/abs/10.1021/ie071206c |
