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Détail de l'auteur
Auteur Jingwen Huang
Documents disponibles écrits par cet auteur
Affiner la rechercheProcess Goose Queue (PGQ)Approaches toward plantwide process optimization with applications in supervision - driven real - time optimization / Hongguang Li in Industrial & engineering chemistry research, Vol. 51 N° 33 (Août 2012)
[article]
in Industrial & engineering chemistry research > Vol. 51 N° 33 (Août 2012) . - pp. 10848–10859
Titre : Process Goose Queue (PGQ)Approaches toward plantwide process optimization with applications in supervision - driven real - time optimization Type de document : texte imprimé Auteurs : Hongguang Li, Auteur ; Jingwen Huang, Auteur Année de publication : 2012 Article en page(s) : pp. 10848–10859 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Plantwide process Optimization Résumé : Inspired by the biologic nature of flying geese, process goose queue (PGQ) approaches toward plantwide process optimization are explicitly introduced in this paper along with applications in real-time optimization (RTO). Taking advantage of ad-hoc PGQ metrics, process variables associated with a process unit could be accordingly identical with geese positions of a PGQ. Motivated by the self-organization in flight formation of geese, a process unit can achieve such an optimum formation that every goose in the PGQ benefits from the maximum upwash. In this sense, adjustment rules invoked to track the ideal PGQ formulation are accommodated. Followed by this idea, a plantwide process is first decomposed into several hierarchically connected multilayer PGQs. Subsequently, a plantwide PGQ which includes a PGQ-objective and several multilayer PGQs is constructed, which contributes to solving complex plantwide process optimization problems in a novel way. As applications of PGQ approaches, we initially address a supervision-driven RTO issue concerning economic performance deterioration caused by process supervision. A process unit whose variables are shifted by human operators can be regarded as an ill-PGQ which would trigger the autonomous adjustments of the plantwide PGQ. Enabling algorithms concerning adjustment sequence of the plantwide PGQ with an ill-PGQ are constructed, which are generally characterized by ill-PGQ detection, PGQ follow-up, and PGQ-objective achievement. To demonstrate the feasibility and validity of this contribution, the Tennessee Eastman (TE) benchmark process is employed as an extensive case study, showing that the proposed approaches particularly enjoy considerable computational simplicity in contrast with traditional global optimization strategies. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie300374g [article] Process Goose Queue (PGQ)Approaches toward plantwide process optimization with applications in supervision - driven real - time optimization [texte imprimé] / Hongguang Li, Auteur ; Jingwen Huang, Auteur . - 2012 . - pp. 10848–10859.
Industrial chemistry
Langues : Anglais (eng)
in Industrial & engineering chemistry research > Vol. 51 N° 33 (Août 2012) . - pp. 10848–10859
Mots-clés : Plantwide process Optimization Résumé : Inspired by the biologic nature of flying geese, process goose queue (PGQ) approaches toward plantwide process optimization are explicitly introduced in this paper along with applications in real-time optimization (RTO). Taking advantage of ad-hoc PGQ metrics, process variables associated with a process unit could be accordingly identical with geese positions of a PGQ. Motivated by the self-organization in flight formation of geese, a process unit can achieve such an optimum formation that every goose in the PGQ benefits from the maximum upwash. In this sense, adjustment rules invoked to track the ideal PGQ formulation are accommodated. Followed by this idea, a plantwide process is first decomposed into several hierarchically connected multilayer PGQs. Subsequently, a plantwide PGQ which includes a PGQ-objective and several multilayer PGQs is constructed, which contributes to solving complex plantwide process optimization problems in a novel way. As applications of PGQ approaches, we initially address a supervision-driven RTO issue concerning economic performance deterioration caused by process supervision. A process unit whose variables are shifted by human operators can be regarded as an ill-PGQ which would trigger the autonomous adjustments of the plantwide PGQ. Enabling algorithms concerning adjustment sequence of the plantwide PGQ with an ill-PGQ are constructed, which are generally characterized by ill-PGQ detection, PGQ follow-up, and PGQ-objective achievement. To demonstrate the feasibility and validity of this contribution, the Tennessee Eastman (TE) benchmark process is employed as an extensive case study, showing that the proposed approaches particularly enjoy considerable computational simplicity in contrast with traditional global optimization strategies. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie300374g