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Subspace - modeling - based nonlinear measurement for process design / XinJiang Lu in Industrial & engineering chemistry research, Vol. 50 N° 23 (Décembre 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 23 (Décembre 2011) . - pp. 13457–13465 Titre : Subspace - modeling - based nonlinear measurement for process design Type de document : texte imprimé Auteurs : XinJiang Lu, Auteur ; MingHui Huang, Auteur ; YiBo Li, Auteur Année de publication : 2012 Article en page(s) : pp. 13457–13465 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Nonlinear  processes Résumé : In industry, many nonlinear processes can be approximated well by a linear model under a suitable design parameter, upon which a linear controller can effectively control these processes. The key problem is how to find this suitable design parameter, which is never considered in process design. In this paper, a novel design for control approach is proposed to design the process to have a satisfactory linear approximation. First, a subspace-modeling-based nonlinear measurement is proposed to avoid the infinite dimensional optimization problem in the traditional nonlinearity measurement. Then a particle-swarm-optimization-based design approach is developed to obtain the optimal design parameter through solving the nonconvex and nondifferential measurement problem. Finally, the proposed design is applied to design a practical curing oven and compared with the existing design. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie2008554 [article] Subspace - modeling - based nonlinear measurement for process design [texte imprimé] / XinJiang Lu, Auteur ; MingHui Huang, Auteur ; YiBo Li, Auteur . - 2012 . - pp. 13457–13465. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 23 (Décembre 2011) . - pp. 13457–13465 Mots-clés : Nonlinear  processes Résumé : In industry, many nonlinear processes can be approximated well by a linear model under a suitable design parameter, upon which a linear controller can effectively control these processes. The key problem is how to find this suitable design parameter, which is never considered in process design. In this paper, a novel design for control approach is proposed to design the process to have a satisfactory linear approximation. First, a subspace-modeling-based nonlinear measurement is proposed to avoid the infinite dimensional optimization problem in the traditional nonlinearity measurement. Then a particle-swarm-optimization-based design approach is developed to obtain the optimal design parameter through solving the nonconvex and nondifferential measurement problem. Finally, the proposed design is applied to design a practical curing oven and compared with the existing design. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie2008554