Documents disponibles écrits par cet auteur

Incremental global parameter estimation in dynamical systems / Michalik, Claas in Industrial & engineering chemistry research, Vol. 48 N° 11 (Juin 2009) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 48 N° 11 (Juin 2009) . - pp. 5489–5497 Titre : Incremental global parameter estimation in dynamical systems Type de document : texte imprimé Auteurs : Michalik, Claas, Auteur ; Benoît Chachuat, Auteur ; Marquardt, Wolfgang, Auteur Année de publication : 2009 Article en page(s) : pp. 5489–5497 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Dynamical  system  Efficient  computational  method  Software  packages  Incremental  identification Résumé : Estimating the parameters of a dynamical system based on measurements is an important task in industrial and scientific practice. Since a model’s quality is directly linked to its parameter values, obtaining globally rather than locally optimal values is especially important in this context. In practice, however, local methods are used almost exclusively. This is mainly due to the high computational cost of global dynamic parameter estimation, which limits its application to relatively small problems comprising no more than a few equations and parameters. In addition, there is still a lack of software packages that allow global parameter estimation in dynamical systems without expert knowledge. Therefore, we propose an efficient computational method for obtaining globally optimal parameter estimates of dynamical systems using well-established, user-friendly software packages. The method is based on the so-called incremental identification procedure, in combination with deterministic global optimization tools for nonlinear programs. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie8015472 [article] Incremental global parameter estimation in dynamical systems [texte imprimé] / Michalik, Claas, Auteur ; Benoît Chachuat, Auteur ; Marquardt, Wolfgang, Auteur . - 2009 . - pp. 5489–5497. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N° 11 (Juin 2009) . - pp. 5489–5497 Mots-clés : Dynamical  system  Efficient  computational  method  Software  packages  Incremental  identification Résumé : Estimating the parameters of a dynamical system based on measurements is an important task in industrial and scientific practice. Since a model’s quality is directly linked to its parameter values, obtaining globally rather than locally optimal values is especially important in this context. In practice, however, local methods are used almost exclusively. This is mainly due to the high computational cost of global dynamic parameter estimation, which limits its application to relatively small problems comprising no more than a few equations and parameters. In addition, there is still a lack of software packages that allow global parameter estimation in dynamical systems without expert knowledge. Therefore, we propose an efficient computational method for obtaining globally optimal parameter estimates of dynamical systems using well-established, user-friendly software packages. The method is based on the so-called incremental identification procedure, in combination with deterministic global optimization tools for nonlinear programs. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie8015472

Optimal experimental design for discriminating numerous model candidates / Michalik, Claas in Industrial & engineering chemistry research, Vol. 49 N° 2 (Janvier 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 2 (Janvier 2010) . - pp 913–919 Titre : Optimal experimental design for discriminating numerous model candidates : the AWDC criterion Type de document : texte imprimé Auteurs : Michalik, Claas, Auteur ; Stuckert, Maxim, Auteur ; Marquardt, Wolfgang, Auteur Année de publication : 2010 Article en page(s) : pp 913–919 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Optimal  experimental  Discriminating  numerous. Résumé : While model-based optimal experimental design (OED) strategies aiming at maximizing the parameter precision are regularly applied in industry and academia, only a little attention has been payed to OED techniques for model discrimination in practical applications. A broader use of these techniques is mainly hindered by two drawbacks: (i) The use of such techniques is desirable in an early model identification phase, where only a little knowledge on the process is available. The known methods, however, rely on good estimates of the parameters of all candidate model structures. (ii) The available methods are tailored to few (ideally two) model candidates and do not work well if numerous candidate structures are taken into account. In this work we propose a novel design criterion for model-based OED for model discrimination in the case of multiple model candidates. The resulting OED method is thus well-suited for designing experiments in an early stage of the model identification process to efficiently reduce the number of model candidates, thereby reducing the overall cost for model identification. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900903u [article] Optimal experimental design for discriminating numerous model candidates : the AWDC criterion [texte imprimé] / Michalik, Claas, Auteur ; Stuckert, Maxim, Auteur ; Marquardt, Wolfgang, Auteur . - 2010 . - pp 913–919. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 2 (Janvier 2010) . - pp 913–919 Mots-clés : Optimal  experimental  Discriminating  numerous. Résumé : While model-based optimal experimental design (OED) strategies aiming at maximizing the parameter precision are regularly applied in industry and academia, only a little attention has been payed to OED techniques for model discrimination in practical applications. A broader use of these techniques is mainly hindered by two drawbacks: (i) The use of such techniques is desirable in an early model identification phase, where only a little knowledge on the process is available. The known methods, however, rely on good estimates of the parameters of all candidate model structures. (ii) The available methods are tailored to few (ideally two) model candidates and do not work well if numerous candidate structures are taken into account. In this work we propose a novel design criterion for model-based OED for model discrimination in the case of multiple model candidates. The resulting OED method is thus well-suited for designing experiments in an early stage of the model identification process to efficiently reduce the number of model candidates, thereby reducing the overall cost for model identification. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900903u