Documents disponibles écrits par cet auteur

Adjoint transfer matrix based decoupling control for multivariable processes / Shen, Yuling in Industrial & engineering chemistry research, Vol. 51 N° 50 (Décembre 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 50 (Décembre 2012) . - pp. 16419-16426 Titre : Adjoint transfer matrix based decoupling control for multivariable processes Type de document : texte imprimé Auteurs : Shen, Yuling, Auteur ; Youxian Sun, Auteur ; Shaoyuan Li, Auteur Année de publication : 2013 Article en page(s) : pp. 16419-16426 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Multivariable  system Résumé : In this paper, a novel decoupling control scheme based on adjoint matrix is proposed. By introducing the concept of characteristic sequence, the characteristic sequence of both the adjoint transfer matrix and the determinant transfer function are derived from that of original process transfer matrix. The adjoint transfer matrix and determinant transfer function are then determined. Finally, the adjoint matrix is selected as a decoupler, and the decentralized controller is designed for the determinant transfer function. The effectiveness of the proposed design approach is verified by three multivariable industrial processes, which shows that it results in better overall performance compared with other methods. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26732169 [article] Adjoint transfer matrix based decoupling control for multivariable processes [texte imprimé] / Shen, Yuling, Auteur ; Youxian Sun, Auteur ; Shaoyuan Li, Auteur . - 2013 . - pp. 16419-16426. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 50 (Décembre 2012) . - pp. 16419-16426 Mots-clés : Multivariable  system Résumé : In this paper, a novel decoupling control scheme based on adjoint matrix is proposed. By introducing the concept of characteristic sequence, the characteristic sequence of both the adjoint transfer matrix and the determinant transfer function are derived from that of original process transfer matrix. The adjoint transfer matrix and determinant transfer function are then determined. Finally, the adjoint matrix is selected as a decoupler, and the decentralized controller is designed for the determinant transfer function. The effectiveness of the proposed design approach is verified by three multivariable industrial processes, which shows that it results in better overall performance compared with other methods. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26732169

A Multiple - time - region (MTR) - based fault subspace decomposition and reconstruction modeling strategy for online fault diagnosis / Zhao, Chunhui in Industrial & engineering chemistry research, Vol. 51 N° 34 (Août 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 34 (Août 2012) . - pp. 11207–11217 Titre : A Multiple - time - region (MTR) - based fault subspace decomposition and reconstruction modeling strategy for online fault diagnosis Type de document : texte imprimé Auteurs : Zhao, Chunhui, Auteur ; Youxian Sun, Auteur ; Gao, Furong, Auteur Année de publication : 2012 Article en page(s) : pp. 11207–11217 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Fault  diagnosis Résumé : Time-varying fault characteristics have not yet been addressed by conventional fault-reconstruction-based modeling methods, which could affect fault diagnosis performance. In the present work, the multiple-time-region (MTR) nature, that is, the multiplicity of fault characteristics along with the process evolution, is proposed and efficiently analyzed for fault diagnosis. First, an automatic time-region-division algorithm is developed that can partition the whole fault process into different local regions according to the changes in fault characteristics. Different local fault characteristics are thus analyzed by building different representative fault feature models in multiple time regions. Following the changing relationships between the fault and normal operation statuses, different fault reconstruction actions are finally taken in different time regions. By a proper time-region division, the proposed method can better model the time-varying fault behaviors and capture the different fault-to-normal reconstruction relationships for fault diagnosis. The feasibility and performance of the proposed method are illustrated with the Tennessee Eastman process, revealing enhanced fault understanding and improved fault diagnosis performance. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie301096x [article] A Multiple - time - region (MTR) - based fault subspace decomposition and reconstruction modeling strategy for online fault diagnosis [texte imprimé] / Zhao, Chunhui, Auteur ; Youxian Sun, Auteur ; Gao, Furong, Auteur . - 2012 . - pp. 11207–11217. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 34 (Août 2012) . - pp. 11207–11217 Mots-clés : Fault  diagnosis Résumé : Time-varying fault characteristics have not yet been addressed by conventional fault-reconstruction-based modeling methods, which could affect fault diagnosis performance. In the present work, the multiple-time-region (MTR) nature, that is, the multiplicity of fault characteristics along with the process evolution, is proposed and efficiently analyzed for fault diagnosis. First, an automatic time-region-division algorithm is developed that can partition the whole fault process into different local regions according to the changes in fault characteristics. Different local fault characteristics are thus analyzed by building different representative fault feature models in multiple time regions. Following the changing relationships between the fault and normal operation statuses, different fault reconstruction actions are finally taken in different time regions. By a proper time-region division, the proposed method can better model the time-varying fault behaviors and capture the different fault-to-normal reconstruction relationships for fault diagnosis. The feasibility and performance of the proposed method are illustrated with the Tennessee Eastman process, revealing enhanced fault understanding and improved fault diagnosis performance. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie301096x

Statistical modeling and online monitoring based on between - set regression analysis / Chunhui Zhao in Industrial & engineering chemistry research, Vol. 51 N° 25 (Juin 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 25 (Juin 2012) . - pp. 8495-8509 Titre : Statistical modeling and online monitoring based on between - set regression analysis Type de document : texte imprimé Auteurs : Chunhui Zhao, Auteur ; Gao, Furong, Auteur ; Youxian Sun, Auteur Année de publication : 2012 Article en page(s) : pp. 8495-8509 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Regression  analysis  Surveillance  Modeling Résumé : In the present work, a monitoring strategy based on between-set regression analysis is developed for the online monitoring of processes with multiple "modes". The definition of modes here differs from the conventional ones in that, the modes here may be different sets of variables collected for the same set of objects (called variable mode) or they may be process measurements collected at different times (called time mode). The subject of analysis includes two predictor data sets, corresponding to two neighboring process modes, and one matrix containing data on quality with which both predictor data sets are associated. The basic assumption is that a certain part of the underlying quality-concemed process variability stays constant despite the changeover of process modes. On the basis of between-set regression analysis, the quality-relevant systematic information in each mode space is decomposed into two parts: the between-mode common subspace and the between-mode specific subspace. The former reveals the between-mode quality-relevant similarity and the latter the dissimilarity. The two parts are then used in the development of an online monitoring system. The feasibility and performance of the proposed method are illustrated with a simple numerical case and a typical multiphase batch process. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26066777 [article] Statistical modeling and online monitoring based on between - set regression analysis [texte imprimé] / Chunhui Zhao, Auteur ; Gao, Furong, Auteur ; Youxian Sun, Auteur . - 2012 . - pp. 8495-8509. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 25 (Juin 2012) . - pp. 8495-8509 Mots-clés : Regression  analysis  Surveillance  Modeling Résumé : In the present work, a monitoring strategy based on between-set regression analysis is developed for the online monitoring of processes with multiple "modes". The definition of modes here differs from the conventional ones in that, the modes here may be different sets of variables collected for the same set of objects (called variable mode) or they may be process measurements collected at different times (called time mode). The subject of analysis includes two predictor data sets, corresponding to two neighboring process modes, and one matrix containing data on quality with which both predictor data sets are associated. The basic assumption is that a certain part of the underlying quality-concemed process variability stays constant despite the changeover of process modes. On the basis of between-set regression analysis, the quality-relevant systematic information in each mode space is decomposed into two parts: the between-mode common subspace and the between-mode specific subspace. The former reveals the between-mode quality-relevant similarity and the latter the dissimilarity. The two parts are then used in the development of an online monitoring system. The feasibility and performance of the proposed method are illustrated with a simple numerical case and a typical multiphase batch process. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26066777