2020 |
Atitallah, Halima; Aribi, Asma; Aoun, Mohamed Diagnosis of time-delay fractional systems using observer-based methods Article de journal Dans: International Journal of Dynamical Systems and Differential Equations, vol. 10, no. 2, p. 128 – 148, 2020, (Cited by: 2). Résumé | Liens | BibTeX | Étiquettes: Convergence conditions, Diagnosis, Fault detection, Fault detection and isolation, Fault isolation, Fractional systems, Luenberger observers, Residual sensitivities, Structured residuals, Time delay, Timing circuits, Unknown input observer @article{Atitallah2020128b,In this paper, two model-based methods are considered for the diagnosis of time-delay fractional systems. Time-delay fractional Luenberger observer without unknown input and time-delay fractional unknown input observer are developed and used for fault detection and isolation. A single observer scheme is needed for fault detection and a bank of generalized (respectively dedicated) observers is required for fault isolation. A theoretical study investigating the convergence condition for each observer-based method in terms of matrix inequalities is presented. Residual sensitivities to faults and to disturbances are studied. Time-delay fractional unknown input observer parameters are computed to obtain structured residuals. This observer ensures unknown input decoupling from the state which results residual insensitive to unknown inputs. Two numerical examples to validate the efficiency of the proposed approaches are given. Copyright © 2020 Inderscience Enterprises Ltd. |
2017 |
Atitallah, Halima; Aribi, Asma; Aoun, Mohamed Diagnosis of time-delay fractional systems Conférence 2017, (Cited by: 3). Résumé | Liens | BibTeX | Étiquettes: Automation, Bilinear matrix inequality, Convergence conditions, Convergence of numerical methods, Delay control systems, Diagnosis, Fault detection, Fault indicators, Fractional systems, Fractional-order systems, Luenberger observers, Model based diagnosis, Numerical methods, Process control, residual, Time delay @conference{Atitallah2017284b,In this paper, a model-based diagnosis method, called Luenberger diagnosis observer, recently developed for fractional order systems, is extended for time-delay fractional systems. A sufficient convergence condition of the fault indicator using Bilinear Matrix Inequalities is detailed. A numerical example illustrating the method’s validity in detecting faults is finally presented. © 2016 IEEE. |
Atitallah, Halima; Aribi, Asma; Aoun, Mohamed Diagnosis of time-delay fractional systems Conférence 2017, (Cited by: 3). Résumé | Liens | BibTeX | Étiquettes: Automation, Bilinear matrix inequality, Convergence conditions, Convergence of numerical methods, Delay control systems, Diagnosis, Fault detection, Fault indicators, Fractional systems, Fractional-order systems, Luenberger observers, Model based diagnosis, Numerical methods, Process control, residual, Time delay @conference{Atitallah2017284,In this paper, a model-based diagnosis method, called Luenberger diagnosis observer, recently developed for fractional order systems, is extended for time-delay fractional systems. A sufficient convergence condition of the fault indicator using Bilinear Matrix Inequalities is detailed. A numerical example illustrating the method’s validity in detecting faults is finally presented. © 2016 IEEE. |
2014 |
Aribi, Asma; Farges, Christophe; Aoun, Mohamed; Melchior, Pierre; Najar, Slaheddine; Abdelkrim, Mohamed Naceur Fault detection based on fractional order models: Application to diagnosis of thermal systems Article de journal Dans: Communications in Nonlinear Science and Numerical Simulation, vol. 19, no. 10, p. 3679 – 3693, 2014, (Cited by: 28). Résumé | Liens | BibTeX | Étiquettes: Computer simulation, Diagnosis, Diagnosis methods, Fault detection, Fractional model, Fractional operators, Fractional order models, Numerical analysis, Reduced precision, Single input multi outputs, Thermal phenomena, Thermal systems @article{Aribi20143679b,The aim of this paper is to propose diagnosis methods based on fractional order models and to validate their efficiency to detect faults occurring in thermal systems. Indeed, it is first shown that fractional operator allows to derive in a straightforward way fractional models for thermal phenomena. In order to apply classical diagnosis methods, such models could be approximated by integer order models, but at the expense of much higher involved parameters and reduced precision. Thus, two diagnosis methods initially developed for integer order models are here extended to handle fractional order models. The first one is the generalized dynamic parity space method and the second one is the Luenberger diagnosis observer. Proposed methods are then applied to a single-input multi-output thermal testing bench and demonstrate the methods efficiency for detecting faults affecting thermal systems. © 2014 Elsevier B.V. |
Aribi, Asma; Farges, Christophe; Aoun, Mohamed; Melchior, Pierre; Najar, Slaheddine; Abdelkrim, Mohamed Naceur Fault detection based on fractional order models: Application to diagnosis of thermal systems Article de journal Dans: Communications in Nonlinear Science and Numerical Simulation, vol. 19, no. 10, p. 3679 – 3693, 2014, (Cited by: 28). Résumé | Liens | BibTeX | Étiquettes: Computer simulation, Diagnosis, Diagnosis methods, Fault detection, Fractional model, Fractional operators, Fractional order models, Numerical analysis, Reduced precision, Single input multi outputs, Thermal phenomena, Thermal systems @article{Aribi20143679,The aim of this paper is to propose diagnosis methods based on fractional order models and to validate their efficiency to detect faults occurring in thermal systems. Indeed, it is first shown that fractional operator allows to derive in a straightforward way fractional models for thermal phenomena. In order to apply classical diagnosis methods, such models could be approximated by integer order models, but at the expense of much higher involved parameters and reduced precision. Thus, two diagnosis methods initially developed for integer order models are here extended to handle fractional order models. The first one is the generalized dynamic parity space method and the second one is the Luenberger diagnosis observer. Proposed methods are then applied to a single-input multi-output thermal testing bench and demonstrate the methods efficiency for detecting faults affecting thermal systems. © 2014 Elsevier B.V. |
Publications
2020 |
Diagnosis of time-delay fractional systems using observer-based methods Article de journal Dans: International Journal of Dynamical Systems and Differential Equations, vol. 10, no. 2, p. 128 – 148, 2020, (Cited by: 2). |
2017 |
Diagnosis of time-delay fractional systems Conférence 2017, (Cited by: 3). |
Diagnosis of time-delay fractional systems Conférence 2017, (Cited by: 3). |
2014 |
Fault detection based on fractional order models: Application to diagnosis of thermal systems Article de journal Dans: Communications in Nonlinear Science and Numerical Simulation, vol. 19, no. 10, p. 3679 – 3693, 2014, (Cited by: 28). |
Fault detection based on fractional order models: Application to diagnosis of thermal systems Article de journal Dans: Communications in Nonlinear Science and Numerical Simulation, vol. 19, no. 10, p. 3679 – 3693, 2014, (Cited by: 28). |