Documents disponibles écrits par cet auteur

Constrained nonlinear state estimation using ensemble kalman filters / J. Prakash in Industrial & engineering chemistry research, Vol. 49 N° 5 (Mars 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 5 (Mars 2010) . - pp. 2242–2253 Titre : Constrained nonlinear state estimation using ensemble kalman filters Type de document : texte imprimé Auteurs : J. Prakash, Auteur ; Sachin C. Patwardhan, Auteur ; Shah, Sirish L., Auteur Année de publication : 2010 Article en page(s) : pp. 2242–2253 Note générale : Industrial Chemistry Langues : Anglais (eng) Mots-clés : EnKF;  kalman Résumé : Recursive estimation of states of constrained nonlinear dynamic systems has attracted the attention of many researchers in recent years. In this work, we propose a constrained recursive formulation of the ensemble Kalman filter (EnKF) that retains the advantages of the unconstrained EnKF while systematically dealing with bounds on the estimated states. The EnKF belongs to the class of particle filters that are increasingly being used for solving state estimation problems associated with nonlinear systems. A highlight of our approach is the use of truncated multivariate distributions for systematically solving the estimation problem in the presence of state constraints. The efficacy of the proposed constrained state estimation algorithm using the EnKF is illustrated by application on two benchmark problems in the literature (a simulated gas-phase reactor and an isothermal batch reactor) involving constraints on estimated state variables and another example problem, which involves constraints on the process noise. Note de contenu : Bibliogr. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900197s [article] Constrained nonlinear state estimation using ensemble kalman filters [texte imprimé] / J. Prakash, Auteur ; Sachin C. Patwardhan, Auteur ; Shah, Sirish L., Auteur . - 2010 . - pp. 2242–2253. Industrial Chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 5 (Mars 2010) . - pp. 2242–2253 Mots-clés : EnKF;  kalman Résumé : Recursive estimation of states of constrained nonlinear dynamic systems has attracted the attention of many researchers in recent years. In this work, we propose a constrained recursive formulation of the ensemble Kalman filter (EnKF) that retains the advantages of the unconstrained EnKF while systematically dealing with bounds on the estimated states. The EnKF belongs to the class of particle filters that are increasingly being used for solving state estimation problems associated with nonlinear systems. A highlight of our approach is the use of truncated multivariate distributions for systematically solving the estimation problem in the presence of state constraints. The efficacy of the proposed constrained state estimation algorithm using the EnKF is illustrated by application on two benchmark problems in the literature (a simulated gas-phase reactor and an isothermal batch reactor) involving constraints on estimated state variables and another example problem, which involves constraints on the process noise. Note de contenu : Bibliogr. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900197s

New approach to develop dynamic gray box model for a plasticating twin-screw extruder / Iqbal, Mohammad H. 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 648–657 Titre : New approach to develop dynamic gray box model for a plasticating twin-screw extruder Type de document : texte imprimé Auteurs : Iqbal, Mohammad H., Auteur ; Sundararaj, Uttandaraman, Auteur ; Shah, Sirish L., Auteur Année de publication : 2010 Article en page(s) : pp 648–657 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Dynamic  Plasticating  TSE  High-density  polyethylenes. Résumé : The dynamic behaviors of the process variables of a twin screw extruder (TSE) have inherent nonlinearity and time delay. Thus, it is important to develop a process model and furthermore to design controllers based on that model for stable operation. A new approach is explained in this work to develop dynamic gray box models to predict the responses of the process output variables due to change in the screw speed (N) for a plasticating TSE. This approach comprises the selection of controlled variables and the development of gray box models relating the selected controlled variables and N. The selection of variables was based on both the steady-state correlation analysis with final product properties and the dynamic considerations. High-density polyethylenes with different melt indices were extruded in a co-rotating TSE in this work. A predesigned random binary sequence type excitation in N was imposed for the dynamic study. Gray box models were developed between two output variables, melt temperature (Tmelt) at die and melt pressure (Pmelt) at die, with N, by incorporating both first principles knowledge of the process and the measured process data using the classical system identification technique. A second-order ARMAX (autoregressive moving average with exogenous input) model was found to be sufficient to capture the dynamic behaviors of Tmelt when N was changed. However, the dynamic behavior of Pmelt was modeled by a third-order ARMAX structure. Both models are in agreement with the a priori process information of the TSE. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900190z [article] New approach to develop dynamic gray box model for a plasticating twin-screw extruder [texte imprimé] / Iqbal, Mohammad H., Auteur ; Sundararaj, Uttandaraman, Auteur ; Shah, Sirish L., Auteur . - 2010 . - pp 648–657. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 2 (Janvier 2010) . - pp 648–657 Mots-clés : Dynamic  Plasticating  TSE  High-density  polyethylenes. Résumé : The dynamic behaviors of the process variables of a twin screw extruder (TSE) have inherent nonlinearity and time delay. Thus, it is important to develop a process model and furthermore to design controllers based on that model for stable operation. A new approach is explained in this work to develop dynamic gray box models to predict the responses of the process output variables due to change in the screw speed (N) for a plasticating TSE. This approach comprises the selection of controlled variables and the development of gray box models relating the selected controlled variables and N. The selection of variables was based on both the steady-state correlation analysis with final product properties and the dynamic considerations. High-density polyethylenes with different melt indices were extruded in a co-rotating TSE in this work. A predesigned random binary sequence type excitation in N was imposed for the dynamic study. Gray box models were developed between two output variables, melt temperature (Tmelt) at die and melt pressure (Pmelt) at die, with N, by incorporating both first principles knowledge of the process and the measured process data using the classical system identification technique. A second-order ARMAX (autoregressive moving average with exogenous input) model was found to be sufficient to capture the dynamic behaviors of Tmelt when N was changed. However, the dynamic behavior of Pmelt was modeled by a third-order ARMAX structure. Both models are in agreement with the a priori process information of the TSE. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900190z