Documents disponibles écrits par cet auteur

Dynamic multimode process modeling and monitoring using adaptive gaussian mixture models / Xiang Xie in Industrial & engineering chemistry research, Vol. 51 N° 15 (Avril 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 15 (Avril 2012) . - pp. 5497-5505 Titre : Dynamic multimode process modeling and monitoring using adaptive gaussian mixture models Type de document : texte imprimé Auteurs : Xiang Xie, Auteur ; Hongbo Shi, Auteur Année de publication : 2012 Article en page(s) : pp. 5497-5505 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Surveillance  Modeling Résumé : For multimode processes, it is inevitable to encounter disturbances, such as equipment aging, catalyst deactivation, sensor drifting, reaction kinetics drifting, or adding new operating modes. The existing monitoring algorithms are established either for coping with multimode feature under time-invariant circumstance or for handling the time-varying problem of processes with single operating mode. The purpose of this article is to develop an effective modeling and monitoring approach for complex processes with both multimode and time-varying properties. We propose a novel adaptive monitoring scheme based on Gaussian Mixture Model (GMM). The new method is able to model different operating modes as well as trace process variations. The effectiveness and efficiency of the new method are validated by a numerical example and the Tennessee Eastman (TE) simulation platform in different scenarios. REFERENCE : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25815828 [article] Dynamic multimode process modeling and monitoring using adaptive gaussian mixture models [texte imprimé] / Xiang Xie, Auteur ; Hongbo Shi, Auteur . - 2012 . - pp. 5497-5505. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 15 (Avril 2012) . - pp. 5497-5505 Mots-clés : Surveillance  Modeling Résumé : For multimode processes, it is inevitable to encounter disturbances, such as equipment aging, catalyst deactivation, sensor drifting, reaction kinetics drifting, or adding new operating modes. The existing monitoring algorithms are established either for coping with multimode feature under time-invariant circumstance or for handling the time-varying problem of processes with single operating mode. The purpose of this article is to develop an effective modeling and monitoring approach for complex processes with both multimode and time-varying properties. We propose a novel adaptive monitoring scheme based on Gaussian Mixture Model (GMM). The new method is able to model different operating modes as well as trace process variations. The effectiveness and efficiency of the new method are validated by a numerical example and the Tennessee Eastman (TE) simulation platform in different scenarios. REFERENCE : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25815828

Local model - based predictive control for spatially - distributed systems based on linear programming / Mengling Wang in Industrial & engineering chemistry research, Vol. 51 N° 29 (Juillet 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 29 (Juillet 2012) . - pp. 9783-9789 Titre : Local model - based predictive control for spatially - distributed systems based on linear programming Type de document : texte imprimé Auteurs : Mengling Wang, Auteur ; Yang Zhang, Auteur ; Hongbo Shi, Auteur Année de publication : 2012 Article en page(s) : pp. 9783-9789 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Mathematical  programming  Linear  programming  Predictive  controlModeling Résumé : A local model-based predictive control strategy based on linear programming is proposed for partial differential equation descriptions unknown spatially distributed systems (SDSs). First, the interval type-2 T-S fuzzy based local modeling approach is developed to estimate the dynamics of the SDS based on the input—output data. On the basis of the local IT2 T-S fuzzy model, the local model-based predictive controller is designed to obtain local controlled outputs through minimizing the local optimization objective. Finally, the global controlled outputs are obtained by a linear programming method, where the deviations of the spatial temporal outputs from their spatial set points over the prediction horizon are considered as the optimal objective. The accuracy and efficiency of the proposed methodologies are tested in the simulation case. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26184957 [article] Local model - based predictive control for spatially - distributed systems based on linear programming [texte imprimé] / Mengling Wang, Auteur ; Yang Zhang, Auteur ; Hongbo Shi, Auteur . - 2012 . - pp. 9783-9789. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 29 (Juillet 2012) . - pp. 9783-9789 Mots-clés : Mathematical  programming  Linear  programming  Predictive  controlModeling Résumé : A local model-based predictive control strategy based on linear programming is proposed for partial differential equation descriptions unknown spatially distributed systems (SDSs). First, the interval type-2 T-S fuzzy based local modeling approach is developed to estimate the dynamics of the SDS based on the input—output data. On the basis of the local IT2 T-S fuzzy model, the local model-based predictive controller is designed to obtain local controlled outputs through minimizing the local optimization objective. Finally, the global controlled outputs are obtained by a linear programming method, where the deviations of the spatial temporal outputs from their spatial set points over the prediction horizon are considered as the optimal objective. The accuracy and efficiency of the proposed methodologies are tested in the simulation case. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26184957