Documents disponibles écrits par cet auteur

Online fault diagnosis in nonlinear systems using the multiple operating regime approach / Anjali P. Deshpande in Industrial & engineering chemistry research, Vol. 47 N°17 (Septembre 2008) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 47 N°17 (Septembre 2008) . - p. 6711–6726 Titre : Online fault diagnosis in nonlinear systems using the multiple operating regime approach Type de document : texte imprimé Auteurs : Anjali P. Deshpande, Auteur ; Sachin C. Patwardhan, Auteur Année de publication : 2008 Article en page(s) : p. 6711–6726 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Nonlinear  systems  Multiple-operating-regimes-based  technique  Bayesian  approach  Generalized  likelihood  ratio  method Résumé : Many chemical processes exhibit highly nonlinear dynamic behavior when operated over a wide operating range. The fault diagnosis schemes based on a linear perturbation model often prove to be inadequate, with regard to addressing fault diagnosis problems in such systems. In this work, a novel multiple-operating-regimes-based technique is proposed for performing online fault diagnosis in nonlinear systems. A Bayesian approach is used to identify the combination of linear perturbation models in different operating regimes that best-represents the plant dynamics at the current operating point. Nonlinear versions of the generalized likelihood ratio (GLR) method that use multiple linear models for fault identification are proposed. The proposed multimodel based fault diagnosis approaches are computationally efficient and exploit the linearity of each submodel. To arrest the performance degradation caused by the occurrence of faults, the information provided by the fault diagnosis component is then used for online fault accommodation. The efficacy of the proposed diagnosis schemes is demonstrated by conducting simulation studies on two benchmark continuously stirred tank reactor (CSTR) systems and a high-purity binary distillation column system. Analysis of the simulation results reveals that the proposed multimodel Kalman filter-based fault diagnosis schemes outperform the linear GLR method when a nonlinear process is in a transient state over a wide operating range. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie071593q [article] Online fault diagnosis in nonlinear systems using the multiple operating regime approach [texte imprimé] / Anjali P. Deshpande, Auteur ; Sachin C. Patwardhan, Auteur . - 2008 . - p. 6711–6726. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 47 N°17 (Septembre 2008) . - p. 6711–6726 Mots-clés : Nonlinear  systems  Multiple-operating-regimes-based  technique  Bayesian  approach  Generalized  likelihood  ratio  method Résumé : Many chemical processes exhibit highly nonlinear dynamic behavior when operated over a wide operating range. The fault diagnosis schemes based on a linear perturbation model often prove to be inadequate, with regard to addressing fault diagnosis problems in such systems. In this work, a novel multiple-operating-regimes-based technique is proposed for performing online fault diagnosis in nonlinear systems. A Bayesian approach is used to identify the combination of linear perturbation models in different operating regimes that best-represents the plant dynamics at the current operating point. Nonlinear versions of the generalized likelihood ratio (GLR) method that use multiple linear models for fault identification are proposed. The proposed multimodel based fault diagnosis approaches are computationally efficient and exploit the linearity of each submodel. To arrest the performance degradation caused by the occurrence of faults, the information provided by the fault diagnosis component is then used for online fault accommodation. The efficacy of the proposed diagnosis schemes is demonstrated by conducting simulation studies on two benchmark continuously stirred tank reactor (CSTR) systems and a high-purity binary distillation column system. Analysis of the simulation results reveals that the proposed multimodel Kalman filter-based fault diagnosis schemes outperform the linear GLR method when a nonlinear process is in a transient state over a wide operating range. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie071593q

Online sensor/actuator failure isolation and reconfigurablecontrol using the generalized likelihood ratio method / Anjali P. Deshpande in Industrial & engineering chemistry research, Vol. 48 N°3 (Février 2009) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 48 N°3 (Février 2009) . - p. 1522–1535 Titre : Online sensor/actuator failure isolation and reconfigurablecontrol using the generalized likelihood ratio method Type de document : texte imprimé Auteurs : Anjali P. Deshpande, Auteur ; Ujjwal Zamad, Auteur ; Sachin C. Patwardhan, Auteur Année de publication : 2009 Article en page(s) : p. 1522–1535 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Sensor  --  Control  Actuator  --  Control  Sensor  failure  Diagnose  online Résumé : In processing plants, sensor and/or actuator failures can have considerable deteriorating effect on the closed-loop performance. Such failures have to be diagnosed online, as quickly as possible, and actively accommodated to arrest the performance degradation. Active failure tolerance can be achieved by employing model-based failure diagnosis techniques and redesigning/restructuring controller online. In this work, a sensor/actuator failure isolation strategy has been developed under the linear generalized likelihood ratio (GLR) framework. The strategy is then extended to isolation of sensor and actuator failures in nonlinear systems. The infomation on sensor/actuator failures is further used for online reconfiguration of the state estimator and the controller/control scheme. In case of sensor failure, the state estimator is reconfigured by removing the measurement of failed sensor from the measurement vector. If an observability property is preserved after sensor failure, then an inferential control scheme is employed subsequent to the failure. When an actuator failure is isolated, it is proposed to make modifications in the controller objectives or switch to a new controller to account for the loss of a degree of freedom. The efficacy of the proposed failure diagnosis and control structure reconfiguration schemes is demonstrated by conducting experimental studies on a benchmark heater mixer set up. Analysis of these results reveals that the proposed strategies are able to isolate the failures accurately and recover the closed-loop performance by online reconfiguration of the controller/control scheme. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie8003122 [article] Online sensor/actuator failure isolation and reconfigurablecontrol using the generalized likelihood ratio method [texte imprimé] / Anjali P. Deshpande, Auteur ; Ujjwal Zamad, Auteur ; Sachin C. Patwardhan, Auteur . - 2009 . - p. 1522–1535. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N°3 (Février 2009) . - p. 1522–1535 Mots-clés : Sensor  --  Control  Actuator  --  Control  Sensor  failure  Diagnose  online Résumé : In processing plants, sensor and/or actuator failures can have considerable deteriorating effect on the closed-loop performance. Such failures have to be diagnosed online, as quickly as possible, and actively accommodated to arrest the performance degradation. Active failure tolerance can be achieved by employing model-based failure diagnosis techniques and redesigning/restructuring controller online. In this work, a sensor/actuator failure isolation strategy has been developed under the linear generalized likelihood ratio (GLR) framework. The strategy is then extended to isolation of sensor and actuator failures in nonlinear systems. The infomation on sensor/actuator failures is further used for online reconfiguration of the state estimator and the controller/control scheme. In case of sensor failure, the state estimator is reconfigured by removing the measurement of failed sensor from the measurement vector. If an observability property is preserved after sensor failure, then an inferential control scheme is employed subsequent to the failure. When an actuator failure is isolated, it is proposed to make modifications in the controller objectives or switch to a new controller to account for the loss of a degree of freedom. The efficacy of the proposed failure diagnosis and control structure reconfiguration schemes is demonstrated by conducting experimental studies on a benchmark heater mixer set up. Analysis of these results reveals that the proposed strategies are able to isolate the failures accurately and recover the closed-loop performance by online reconfiguration of the controller/control scheme. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie8003122