2022
|
Dadi, Leila; Ethabet, Haifa; Aoun, Mohamed Set-Membership Fault Detection for Discrete-time Switched Linear Systems Conférence 2022, (Cited by: 0). @conference{Dadi2022190b,
title = {Set-Membership Fault Detection for Discrete-time Switched Linear Systems},
author = {Leila Dadi and Haifa Ethabet and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143822450\&doi=10.1109%2fSSD54932.2022.9955834\&partnerID=40\&md5=845297a35126246541ad5d43c4f68b5e},
doi = {10.1109/SSD54932.2022.9955834},
year = {2022},
date = {2022-01-01},
journal = {2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022},
pages = {190 \textendash 194},
abstract = {This work deals with Fault Detection (FD) for a class of discrete-time switched linear systems with actuator faults subject to bounded disturbances. First, based on cooperativity and stability conditions and under the assumption that disturbances and measurement noise are unknown but bounded, upper and lower bounds of the state are calculated using an interval observer. The design conditions of the observer are expressed in terms of Linear Matrix Inequalities (LMIs). Second, a fault detection decision is developed to indicate the presence of faults using interval analysis. Simulation results are provided to illustrate the performance of the proposed fault detection approach. © 2022 IEEE.},
note = {Cited by: 0},
keywords = {Actuator fault, Actuators, Bounded disturbances, Cooperativity, Discrete time, Fault detection, Faults detection, Interval observers, Linear matrix inequalities, Linear systems, Set-membership, Stability condition, Switched linear system, Switched system},
pubstate = {published},
tppubtype = {conference}
}
This work deals with Fault Detection (FD) for a class of discrete-time switched linear systems with actuator faults subject to bounded disturbances. First, based on cooperativity and stability conditions and under the assumption that disturbances and measurement noise are unknown but bounded, upper and lower bounds of the state are calculated using an interval observer. The design conditions of the observer are expressed in terms of Linear Matrix Inequalities (LMIs). Second, a fault detection decision is developed to indicate the presence of faults using interval analysis. Simulation results are provided to illustrate the performance of the proposed fault detection approach. © 2022 IEEE. |
Lamouchi, Rihab; Amairi, Messaoud; Raissi, Tarek; Aoun, Mohamed Robust Fault Detection based on Zonotopic Observers for Linear Parameter Varying Systems Conférence 2022, (Cited by: 1). @conference{Lamouchi2022773b,
title = {Robust Fault Detection based on Zonotopic Observers for Linear Parameter Varying Systems},
author = {Rihab Lamouchi and Messaoud Amairi and Tarek Raissi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136283232\&doi=10.1109%2fMED54222.2022.9837269\&partnerID=40\&md5=0f45c413f1fc67c6778e347ed65a2432},
doi = {10.1109/MED54222.2022.9837269},
year = {2022},
date = {2022-01-01},
journal = {2022 30th Mediterranean Conference on Control and Automation, MED 2022},
pages = {773 \textendash 778},
abstract = {In this paper, zonotopic fault detection methodology is proposed for a class of discrete-Time Linear Parameter Varying (LPV) systems with sensor faults. The disturbances and measurement noise are assumed to be unknown but bounded by zonotope. First, a fault detection observer is designed based on L? performance to attenuate the effects of the uncertainties and to improve the accuracy of the proposed residual framers. Then, the fault sensitivity is taken into account by measuring H-performance and zonotopic residual evaluation is presented. Finally, the effectiveness of the proposed method is demonstrated by a numerical example. © 2022 IEEE.},
note = {Cited by: 1},
keywords = {Discrete time, Fault detection, Faults detection, Linear parameter varying systems, Linear systems, Measurement Noise, Numerical methods, Performance, Robust fault detection, Sensors faults, Uncertainty, Unknown but bounded, Zonotopes},
pubstate = {published},
tppubtype = {conference}
}
In this paper, zonotopic fault detection methodology is proposed for a class of discrete-Time Linear Parameter Varying (LPV) systems with sensor faults. The disturbances and measurement noise are assumed to be unknown but bounded by zonotope. First, a fault detection observer is designed based on L? performance to attenuate the effects of the uncertainties and to improve the accuracy of the proposed residual framers. Then, the fault sensitivity is taken into account by measuring H-performance and zonotopic residual evaluation is presented. Finally, the effectiveness of the proposed method is demonstrated by a numerical example. © 2022 IEEE. |
Lamouchi, Rihab; Raissi, Tarek; Amairi, Messaoud; Aoun, Mohamed Interval Observers Fault Detection for Linear Parameter Varying Systems with H- Fault Sensitivity Conférence 2022, (Cited by: 1). @conference{Lamouchi2022178b,
title = {Interval Observers Fault Detection for Linear Parameter Varying Systems with H- Fault Sensitivity},
author = {Rihab Lamouchi and Tarek Raissi and Messaoud Amairi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143817218\&doi=10.1109%2fSSD54932.2022.9955878\&partnerID=40\&md5=861234ea09d7f66ce9fcabebfd66668e},
doi = {10.1109/SSD54932.2022.9955878},
year = {2022},
date = {2022-01-01},
journal = {2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022},
pages = {178 \textendash 183},
abstract = {A fault detection (FD) method for a class of discrete-time Linear Parameter Varying (LPV) systems with sensor faults and measurement noise is proposed in this paper. Then, an interval FD observer is studied using Linfty performance to minimise the uncertainties effects and to improve the estimation accuracy. Furthermore, mathcalH- performance is considered in order to calculate the sensitivity of the residual to sensor faults and a FD decision is set to indicate their presence. The validity of the proposed methodology is demonstrated using a numerical example. © 2022 IEEE.},
note = {Cited by: 1},
keywords = {Detection methods, Fault detection, Fault sensitivity, Faults detection, Finite difference method, H- fault sensitivity, Interval observers, Linear parameter varying systems, Linear systems, L∞ performance, Sensor fault detection, Sensors faults, ∞performance},
pubstate = {published},
tppubtype = {conference}
}
A fault detection (FD) method for a class of discrete-time Linear Parameter Varying (LPV) systems with sensor faults and measurement noise is proposed in this paper. Then, an interval FD observer is studied using Linfty performance to minimise the uncertainties effects and to improve the estimation accuracy. Furthermore, mathcalH- performance is considered in order to calculate the sensitivity of the residual to sensor faults and a FD decision is set to indicate their presence. The validity of the proposed methodology is demonstrated using a numerical example. © 2022 IEEE. |
Dadi, Leila; Ethabet, Haifa; Aoun, Mohamed Set-Membership Fault Detection for Discrete-time Switched Linear Systems Conférence 2022, (Cited by: 0). @conference{Dadi2022190,
title = {Set-Membership Fault Detection for Discrete-time Switched Linear Systems},
author = {Leila Dadi and Haifa Ethabet and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143822450\&doi=10.1109%2fSSD54932.2022.9955834\&partnerID=40\&md5=845297a35126246541ad5d43c4f68b5e},
doi = {10.1109/SSD54932.2022.9955834},
year = {2022},
date = {2022-01-01},
journal = {2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022},
pages = {190 \textendash 194},
abstract = {This work deals with Fault Detection (FD) for a class of discrete-time switched linear systems with actuator faults subject to bounded disturbances. First, based on cooperativity and stability conditions and under the assumption that disturbances and measurement noise are unknown but bounded, upper and lower bounds of the state are calculated using an interval observer. The design conditions of the observer are expressed in terms of Linear Matrix Inequalities (LMIs). Second, a fault detection decision is developed to indicate the presence of faults using interval analysis. Simulation results are provided to illustrate the performance of the proposed fault detection approach. © 2022 IEEE.},
note = {Cited by: 0},
keywords = {Actuator fault, Actuators, Bounded disturbances, Cooperativity, Discrete time, Fault detection, Faults detection, Interval observers, Linear matrix inequalities, Linear systems, Set-membership, Stability condition, Switched linear system, Switched system},
pubstate = {published},
tppubtype = {conference}
}
This work deals with Fault Detection (FD) for a class of discrete-time switched linear systems with actuator faults subject to bounded disturbances. First, based on cooperativity and stability conditions and under the assumption that disturbances and measurement noise are unknown but bounded, upper and lower bounds of the state are calculated using an interval observer. The design conditions of the observer are expressed in terms of Linear Matrix Inequalities (LMIs). Second, a fault detection decision is developed to indicate the presence of faults using interval analysis. Simulation results are provided to illustrate the performance of the proposed fault detection approach. © 2022 IEEE. |
2020
|
Ethabet, Haifa; Raissi, Tarek; Amairi, Messaoud; Aoun, Mohamed Fault Detection and Isolation for Continuous-Time Switched Linear Systems: A Set Membership Approach Conférence 2020, (Cited by: 1). @conference{Ethabet2020279b,
title = {Fault Detection and Isolation for Continuous-Time Switched Linear Systems: A Set Membership Approach},
author = {Haifa Ethabet and Tarek Raissi and Messaoud Amairi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103019738\&doi=10.1109%2fSSD49366.2020.9364097\&partnerID=40\&md5=e2297b397f94ac2755b2faf5d9e3ab2e},
doi = {10.1109/SSD49366.2020.9364097},
year = {2020},
date = {2020-01-01},
journal = {Proceedings of the 17th International Multi-Conference on Systems, Signals and Devices, SSD 2020},
pages = {279 \textendash 284},
abstract = {In this paper, the problem of Fault Detection and Isolation (FDI) is investigated for continuous-Time switched linear systems via a set-membership approach. Under the fulfillment of the relative degree property by all the subsystems, the proposed solution is based on the use of a bank of interval unknown input observers. Under the assumption that disturbances and measurement noise are unknown but bounded with a priori known bounds, cooperativity and stability conditions are given in terms of Linear Matrix Inequalities (LMIs) with the fulfillment of an Average Dwell Time (ADT) constraints. Then, upper and lower residuals are computed. A numerical example illustrating the validity of the method in fault detection and isolation is given. © 2020 IEEE.},
note = {Cited by: 1},
keywords = {Average dwell time, Continuous time systems, Fault detection, Fault detection and isolation, Linear matrix inequalities, Linear systems, Measurement Noise, Numerical methods, Set membership approach, Stability condition, Switched linear system, Unknown but bounded, Unknown input observer},
pubstate = {published},
tppubtype = {conference}
}
In this paper, the problem of Fault Detection and Isolation (FDI) is investigated for continuous-Time switched linear systems via a set-membership approach. Under the fulfillment of the relative degree property by all the subsystems, the proposed solution is based on the use of a bank of interval unknown input observers. Under the assumption that disturbances and measurement noise are unknown but bounded with a priori known bounds, cooperativity and stability conditions are given in terms of Linear Matrix Inequalities (LMIs) with the fulfillment of an Average Dwell Time (ADT) constraints. Then, upper and lower residuals are computed. A numerical example illustrating the validity of the method in fault detection and isolation is given. © 2020 IEEE. |
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). @article{Atitallah2020128b,
title = {Diagnosis of time-delay fractional systems using observer-based methods},
author = {Halima Atitallah and Asma Aribi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082651176\&doi=10.1504%2fIJDSDE.2020.106028\&partnerID=40\&md5=65e5911ee7fb678504ed4979565642ee},
doi = {10.1504/IJDSDE.2020.106028},
year = {2020},
date = {2020-01-01},
journal = {International Journal of Dynamical Systems and Differential Equations},
volume = {10},
number = {2},
pages = {128 \textendash 148},
abstract = {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.},
note = {Cited by: 2},
keywords = {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},
pubstate = {published},
tppubtype = {article}
}
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. |
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). @article{Atitallah2020128,
title = {Diagnosis of time-delay fractional systems using observer-based methods},
author = {Halima Atitallah and Asma Aribi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082651176\&doi=10.1504%2fIJDSDE.2020.106028\&partnerID=40\&md5=65e5911ee7fb678504ed4979565642ee},
doi = {10.1504/IJDSDE.2020.106028},
year = {2020},
date = {2020-01-01},
journal = {International Journal of Dynamical Systems and Differential Equations},
volume = {10},
number = {2},
pages = {128 \textendash 148},
abstract = {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.},
note = {Cited by: 2},
keywords = {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},
pubstate = {published},
tppubtype = {article}
}
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. |
2019
|
Atitallah, Halima; Aribi, Asma; Aoun, Mohamed Fault estimation using adaptive observer-based technique for time delay fractional-order systems Conférence 2019, (Cited by: 0). @conference{Atitallah2019399b,
title = {Fault estimation using adaptive observer-based technique for time delay fractional-order systems},
author = {Halima Atitallah and Asma Aribi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074421838\&doi=10.1109%2fASET.2019.8871006\&partnerID=40\&md5=ee4994e2c9873cf3aca7262af2383d7b},
doi = {10.1109/ASET.2019.8871006},
year = {2019},
date = {2019-01-01},
journal = {Proceedings of International Conference on Advanced Systems and Emergent Technologies, IC_ASET 2019},
pages = {399 \textendash 405},
abstract = {This paper proposes a technique to detect and estimate faults for fractional-order systems with time delay. Two observers are used in this method. Indeed, a time-delay fractional Luenberger observer is generated to detect fault. An adaptive fractional order with time delay observer is then constructed to estimate the fault by providing an on-line estimation algorithm. The convergence criteria of this observer is expressed via linear matrix inequalities (LMIs) by the use of a specific Lyapunov function considering the continuous frequency disturbed model. The validity of the fault detection and estimation technique is shown by a numerical example. © 2019 IEEE.},
note = {Cited by: 0},
keywords = {Adaptive observer, Continuous frequency, Convergence criterion, Detection and estimation, Fault detection, Fault estimation, Fractional systems, Fractional-order systems, Linear matrix inequalities, Luenberger observers, Lyapunov functions, Numerical methods, Time delay, Timing circuits},
pubstate = {published},
tppubtype = {conference}
}
This paper proposes a technique to detect and estimate faults for fractional-order systems with time delay. Two observers are used in this method. Indeed, a time-delay fractional Luenberger observer is generated to detect fault. An adaptive fractional order with time delay observer is then constructed to estimate the fault by providing an on-line estimation algorithm. The convergence criteria of this observer is expressed via linear matrix inequalities (LMIs) by the use of a specific Lyapunov function considering the continuous frequency disturbed model. The validity of the fault detection and estimation technique is shown by a numerical example. © 2019 IEEE. |
Ethabet, Haifa; Raïssi, Tarek; Amairi, Messaoud; Aoun, Mohamed Set-Membership Fault Detection for Continuous-time Switched Linear Systems Conférence 2019, (Cited by: 7). @conference{Ethabet2019406b,
title = {Set-Membership Fault Detection for Continuous-time Switched Linear Systems},
author = {Haifa Ethabet and Tarek Ra\"{i}ssi and Messaoud Amairi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074402785\&doi=10.1109%2fASET.2019.8870992\&partnerID=40\&md5=d92dcb337b52e6a06fd5caf02b00c0c0},
doi = {10.1109/ASET.2019.8870992},
year = {2019},
date = {2019-01-01},
journal = {Proceedings of International Conference on Advanced Systems and Emergent Technologies, IC_ASET 2019},
pages = {406 \textendash 411},
abstract = {The problem of Fault Detection (FD) for continuous-time switched linear systems subject to bounded disturbances is investigated in this paper. Based on cooperativity and stability properties, and fulfillment of an Average Dwell Time (ADT) constraint, guaranteed upper and lower bounds of the state are calculated using an interval observer. Under the assumption that disturbances and measurement noise are unknown but bounded with a priori known bounds, stability criteria is expressed in terms of Linear Matrix Inequalities (LMIs). Then, a fault detection methodology is developed to indicate the presence of faults. Finally, we demonstrate the proposed fault detection approach via an illustrative example. © 2019 IEEE.},
note = {Cited by: 7},
keywords = {Bounded disturbances, Continuous time systems, Continuous-time, Fault detection, Linear matrix inequalities, Linear systems, Set membership, Stability criteria, Stability properties, Switched linear system, Switched system, Unknown but bounded, Upper and lower bounds},
pubstate = {published},
tppubtype = {conference}
}
The problem of Fault Detection (FD) for continuous-time switched linear systems subject to bounded disturbances is investigated in this paper. Based on cooperativity and stability properties, and fulfillment of an Average Dwell Time (ADT) constraint, guaranteed upper and lower bounds of the state are calculated using an interval observer. Under the assumption that disturbances and measurement noise are unknown but bounded with a priori known bounds, stability criteria is expressed in terms of Linear Matrix Inequalities (LMIs). Then, a fault detection methodology is developed to indicate the presence of faults. Finally, we demonstrate the proposed fault detection approach via an illustrative example. © 2019 IEEE. |
Atitallah, Halima; Aribi, Asma; Aoun, Mohamed Fault estimation using adaptive observer-based technique for time delay fractional-order systems Conférence 2019, (Cited by: 0). @conference{Atitallah2019399,
title = {Fault estimation using adaptive observer-based technique for time delay fractional-order systems},
author = {Halima Atitallah and Asma Aribi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074421838\&doi=10.1109%2fASET.2019.8871006\&partnerID=40\&md5=ee4994e2c9873cf3aca7262af2383d7b},
doi = {10.1109/ASET.2019.8871006},
year = {2019},
date = {2019-01-01},
journal = {Proceedings of International Conference on Advanced Systems and Emergent Technologies, IC_ASET 2019},
pages = {399 \textendash 405},
abstract = {This paper proposes a technique to detect and estimate faults for fractional-order systems with time delay. Two observers are used in this method. Indeed, a time-delay fractional Luenberger observer is generated to detect fault. An adaptive fractional order with time delay observer is then constructed to estimate the fault by providing an on-line estimation algorithm. The convergence criteria of this observer is expressed via linear matrix inequalities (LMIs) by the use of a specific Lyapunov function considering the continuous frequency disturbed model. The validity of the fault detection and estimation technique is shown by a numerical example. © 2019 IEEE.},
note = {Cited by: 0},
keywords = {Adaptive observer, Continuous frequency, Convergence criterion, Detection and estimation, Fault detection, Fault estimation, Fractional systems, Fractional-order systems, Linear matrix inequalities, Luenberger observers, Lyapunov functions, Numerical methods, Time delay, Timing circuits},
pubstate = {published},
tppubtype = {conference}
}
This paper proposes a technique to detect and estimate faults for fractional-order systems with time delay. Two observers are used in this method. Indeed, a time-delay fractional Luenberger observer is generated to detect fault. An adaptive fractional order with time delay observer is then constructed to estimate the fault by providing an on-line estimation algorithm. The convergence criteria of this observer is expressed via linear matrix inequalities (LMIs) by the use of a specific Lyapunov function considering the continuous frequency disturbed model. The validity of the fault detection and estimation technique is shown by a numerical example. © 2019 IEEE. |
2018
|
Houiji, Marwa; Hamdaoui, Rim; Aoun, Mohamed Fault diagnosis and fault tolerant control against simultaneous sensor and actuator faults for linear stochastic systems Conférence 2018, (Cited by: 1). @conference{Houiji2018810b,
title = {Fault diagnosis and fault tolerant control against simultaneous sensor and actuator faults for linear stochastic systems},
author = {Marwa Houiji and Rim Hamdaoui and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060587807\&doi=10.1109%2fSSD.2018.8570481\&partnerID=40\&md5=2374c560f4bc8c459a08488691d1ba21},
doi = {10.1109/SSD.2018.8570481},
year = {2018},
date = {2018-01-01},
journal = {2018 15th International Multi-Conference on Systems, Signals and Devices, SSD 2018},
pages = {810 \textendash 815},
abstract = {This paper presents the problem of robust fault diagnosis and accommodation for a class of linear stochastic systems where simultaneous actuator and sensor faults may occur at a given time. Firstly, based on Augmented Robust Three stage Kalman filters (ARThSKF) we obtained both the fault estimation and the residual signal. Then, residual evaluation is achieved by making use of an adaptive threshold adjustment algorithm based on the grey theory. Obtained results show that the false-alarm rates and the missing alarm rates are minimized by the developed method; also this approach detects small or incipient faults more effectively than the classical robust fault detection algorithms with fixed thresholds. Finally, an additive control input is introduced for cancelling out the fault's effect on the system. We evaluate our proposal through simulation and we demonstrate its feasibility. © 2018 IEEE.},
note = {Cited by: 1},
keywords = {Actuator and sensor faults, Actuators, Adaptive threshold adjustments, Adaptive thresholds, ARThSK, Failure analysis, Fault accommodation, Fault detection, Linear stochastic system, Robust fault detection, Robust fault diagnosis, Stochastic control systems, Stochastic systems},
pubstate = {published},
tppubtype = {conference}
}
This paper presents the problem of robust fault diagnosis and accommodation for a class of linear stochastic systems where simultaneous actuator and sensor faults may occur at a given time. Firstly, based on Augmented Robust Three stage Kalman filters (ARThSKF) we obtained both the fault estimation and the residual signal. Then, residual evaluation is achieved by making use of an adaptive threshold adjustment algorithm based on the grey theory. Obtained results show that the false-alarm rates and the missing alarm rates are minimized by the developed method; also this approach detects small or incipient faults more effectively than the classical robust fault detection algorithms with fixed thresholds. Finally, an additive control input is introduced for cancelling out the fault’s effect on the system. We evaluate our proposal through simulation and we demonstrate its feasibility. © 2018 IEEE. |
Houiji, Marwa; Hamdaoui, Rim; Aoun, Mohamed Fault diagnosis and fault tolerant control against simultaneous sensor and actuator faults for linear stochastic systems Conférence 2018, (Cited by: 1). @conference{Houiji2018810,
title = {Fault diagnosis and fault tolerant control against simultaneous sensor and actuator faults for linear stochastic systems},
author = {Marwa Houiji and Rim Hamdaoui and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060587807\&doi=10.1109%2fSSD.2018.8570481\&partnerID=40\&md5=2374c560f4bc8c459a08488691d1ba21},
doi = {10.1109/SSD.2018.8570481},
year = {2018},
date = {2018-01-01},
journal = {2018 15th International Multi-Conference on Systems, Signals and Devices, SSD 2018},
pages = {810 \textendash 815},
abstract = {This paper presents the problem of robust fault diagnosis and accommodation for a class of linear stochastic systems where simultaneous actuator and sensor faults may occur at a given time. Firstly, based on Augmented Robust Three stage Kalman filters (ARThSKF) we obtained both the fault estimation and the residual signal. Then, residual evaluation is achieved by making use of an adaptive threshold adjustment algorithm based on the grey theory. Obtained results show that the false-alarm rates and the missing alarm rates are minimized by the developed method; also this approach detects small or incipient faults more effectively than the classical robust fault detection algorithms with fixed thresholds. Finally, an additive control input is introduced for cancelling out the fault's effect on the system. We evaluate our proposal through simulation and we demonstrate its feasibility. © 2018 IEEE.},
note = {Cited by: 1},
keywords = {Actuator and sensor faults, Actuators, Adaptive threshold adjustments, Adaptive thresholds, ARThSK, Failure analysis, Fault accommodation, Fault detection, Linear stochastic system, Robust fault detection, Robust fault diagnosis, Stochastic control systems, Stochastic systems},
pubstate = {published},
tppubtype = {conference}
}
This paper presents the problem of robust fault diagnosis and accommodation for a class of linear stochastic systems where simultaneous actuator and sensor faults may occur at a given time. Firstly, based on Augmented Robust Three stage Kalman filters (ARThSKF) we obtained both the fault estimation and the residual signal. Then, residual evaluation is achieved by making use of an adaptive threshold adjustment algorithm based on the grey theory. Obtained results show that the false-alarm rates and the missing alarm rates are minimized by the developed method; also this approach detects small or incipient faults more effectively than the classical robust fault detection algorithms with fixed thresholds. Finally, an additive control input is introduced for cancelling out the fault’s effect on the system. We evaluate our proposal through simulation and we demonstrate its feasibility. © 2018 IEEE. |
2017
|
Atitallah, Halima; Aribi, Asma; Aoun, Mohamed Diagnosis of time-delay fractional systems Conférence 2017, (Cited by: 3). @conference{Atitallah2017284b,
title = {Diagnosis of time-delay fractional systems},
author = {Halima Atitallah and Asma Aribi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85024400530\&doi=10.1109%2fSTA.2016.7952042\&partnerID=40\&md5=7df0719cec19ecdfbff3cbb2ec3bfeda},
doi = {10.1109/STA.2016.7952042},
year = {2017},
date = {2017-01-01},
journal = {2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Proceedings},
pages = {284 \textendash 292},
abstract = {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.},
note = {Cited by: 3},
keywords = {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},
pubstate = {published},
tppubtype = {conference}
}
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). @conference{Atitallah2017284,
title = {Diagnosis of time-delay fractional systems},
author = {Halima Atitallah and Asma Aribi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85024400530\&doi=10.1109%2fSTA.2016.7952042\&partnerID=40\&md5=7df0719cec19ecdfbff3cbb2ec3bfeda},
doi = {10.1109/STA.2016.7952042},
year = {2017},
date = {2017-01-01},
journal = {2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Proceedings},
pages = {284 \textendash 292},
abstract = {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.},
note = {Cited by: 3},
keywords = {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},
pubstate = {published},
tppubtype = {conference}
}
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. |
2016
|
Houiji, Marwa; Hamdaoui, Rim; Aoun, Mohamed Fault detection performances analysis for stochastic systems based on adaptive threshold Conférence 2016, (Cited by: 2). @conference{Houiji2016229b,
title = {Fault detection performances analysis for stochastic systems based on adaptive threshold},
author = {Marwa Houiji and Rim Hamdaoui and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84974575297\&doi=10.1109%2fSSD.2016.7473701\&partnerID=40\&md5=0f9cdd28ba3852316e53997164690401},
doi = {10.1109/SSD.2016.7473701},
year = {2016},
date = {2016-01-01},
journal = {13th International Multi-Conference on Systems, Signals and Devices, SSD 2016},
pages = {229 \textendash 234},
abstract = {This paper investigates the problem of fault detection for discrete linear systems subjected to unknown disturbances, actuator and sensor faults. A bank of Augmented Robust Three stage Kalman filters is adapted to estimate both the state and the fault as well as to generate the residuals. Besides, this paper presents the evaluation of the residuals with Bayes test of binary hypothesis test for fault detection to adaptive threshold compared with fixed threshold. This test allow the detection of low magnitude faults as fast as possible with a minimum risk of errors, the increase of detection probability and the reduction of false alarm probability. © 2016 IEEE.},
note = {Cited by: 2},
keywords = {Actuator and sensor faults, Adaptive thresholds, Binary hypothesis tests, Detection delays, Detection performance, Detection probabilities, Discrete linear systems, False alarm probability, Fault detection, Linear systems, Signal detection, Stochastic systems},
pubstate = {published},
tppubtype = {conference}
}
This paper investigates the problem of fault detection for discrete linear systems subjected to unknown disturbances, actuator and sensor faults. A bank of Augmented Robust Three stage Kalman filters is adapted to estimate both the state and the fault as well as to generate the residuals. Besides, this paper presents the evaluation of the residuals with Bayes test of binary hypothesis test for fault detection to adaptive threshold compared with fixed threshold. This test allow the detection of low magnitude faults as fast as possible with a minimum risk of errors, the increase of detection probability and the reduction of false alarm probability. © 2016 IEEE. |
Houiji, Marwa; Hamdaoui, Rim; Aoun, Mohamed Fault detection performances analysis for stochastic systems based on adaptive threshold Conférence 2016, (Cited by: 2). @conference{Houiji2016229,
title = {Fault detection performances analysis for stochastic systems based on adaptive threshold},
author = {Marwa Houiji and Rim Hamdaoui and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84974575297\&doi=10.1109%2fSSD.2016.7473701\&partnerID=40\&md5=0f9cdd28ba3852316e53997164690401},
doi = {10.1109/SSD.2016.7473701},
year = {2016},
date = {2016-01-01},
journal = {13th International Multi-Conference on Systems, Signals and Devices, SSD 2016},
pages = {229 \textendash 234},
abstract = {This paper investigates the problem of fault detection for discrete linear systems subjected to unknown disturbances, actuator and sensor faults. A bank of Augmented Robust Three stage Kalman filters is adapted to estimate both the state and the fault as well as to generate the residuals. Besides, this paper presents the evaluation of the residuals with Bayes test of binary hypothesis test for fault detection to adaptive threshold compared with fixed threshold. This test allow the detection of low magnitude faults as fast as possible with a minimum risk of errors, the increase of detection probability and the reduction of false alarm probability. © 2016 IEEE.},
note = {Cited by: 2},
keywords = {Actuator and sensor faults, Adaptive thresholds, Binary hypothesis tests, Detection delays, Detection performance, Detection probabilities, Discrete linear systems, False alarm probability, Fault detection, Linear systems, Signal detection, Stochastic systems},
pubstate = {published},
tppubtype = {conference}
}
This paper investigates the problem of fault detection for discrete linear systems subjected to unknown disturbances, actuator and sensor faults. A bank of Augmented Robust Three stage Kalman filters is adapted to estimate both the state and the fault as well as to generate the residuals. Besides, this paper presents the evaluation of the residuals with Bayes test of binary hypothesis test for fault detection to adaptive threshold compared with fixed threshold. This test allow the detection of low magnitude faults as fast as possible with a minimum risk of errors, the increase of detection probability and the reduction of false alarm probability. © 2016 IEEE. |
2015
|
Yousfi, B.; Raïssi, T.; Amairi, M.; Aoun, M. Set-membership methodology for model-based systems prognosis Conférence vol. 28, no. 21, 2015, (Cited by: 3; All Open Access, Bronze Open Access). @conference{Yousfi2015302b,
title = {Set-membership methodology for model-based systems prognosis},
author = {B. Yousfi and T. Ra\"{i}ssi and M. Amairi and M. Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992504087\&doi=10.1016%2fj.ifacol.2015.09.544\&partnerID=40\&md5=7e3ccad3284ae336ba3fa70c7e9a83fd},
doi = {10.1016/j.ifacol.2015.09.544},
year = {2015},
date = {2015-01-01},
journal = {IFAC-PapersOnLine},
volume = {28},
number = {21},
pages = {302 \textendash 307},
abstract = {This paper addresses unknown input interval estimation and prognosis for a class of uncertain systems. Under the assumption that the measurement noise and the disturbances are bounded, lower and upper bounds for the unmeasured state and unknown inputs are computed. Then, damage state estimation is formulated as a set-inversion problem. The setmembership methodology is applied to an electromechanical oscillator to show the effectiveness of the proposed technique. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.},
note = {Cited by: 3; All Open Access, Bronze Open Access},
keywords = {Fault detection, Interval estimation, Interval observers, Lower and upper bounds, Measurement Noise, Model-based systems, nocv1, Plant management, Set membership, Unknown input observer, Unknown inputs},
pubstate = {published},
tppubtype = {conference}
}
This paper addresses unknown input interval estimation and prognosis for a class of uncertain systems. Under the assumption that the measurement noise and the disturbances are bounded, lower and upper bounds for the unmeasured state and unknown inputs are computed. Then, damage state estimation is formulated as a set-inversion problem. The setmembership methodology is applied to an electromechanical oscillator to show the effectiveness of the proposed technique. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. |
2014
|
Houiji, Marwa; Hamdaoui, Rim; Aoun, Mohamed Detection time for deterministic and stochastic systems with unknown inputs Conférence 2014, (Cited by: 1). @conference{Houiji2014b,
title = {Detection time for deterministic and stochastic systems with unknown inputs},
author = {Marwa Houiji and Rim Hamdaoui and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946686815\&doi=10.1109%2fCISTEM.2014.7076982\&partnerID=40\&md5=0be64cd709ae198f91a4d2b9aecc2dae},
doi = {10.1109/CISTEM.2014.7076982},
year = {2014},
date = {2014-01-01},
journal = {2014 International Conference on Electrical Sciences and Technologies in Maghreb, CISTEM 2014},
abstract = {This paper investigates the detection and diagnosis of actuator faults by using an Unknown Input Observer (UIO).The proposed UIO design guarantees robust residual generation through decoupling the disturbances effects from the faults ones. The discrimination between the faults and the effects of uncertain signals and perturbations on the residues minimizes the duration of fault detection for deterministic systems. Then these results were extended to the general case of stochastic linear systems by using an optimal observers for systems with unknown disturbances and noise. A simulation is done on an aeronautic model to illustrate the theoretical development. © 2014 IEEE.},
note = {Cited by: 1},
keywords = {Detection and diagnosis, Deterministic systems, Fault detection, Linear systems, Optimal observers, Robust residuals, Stochastic linear systems, Stochastic systems, Theoretical development, Unknown disturbance, Unknown input observer},
pubstate = {published},
tppubtype = {conference}
}
This paper investigates the detection and diagnosis of actuator faults by using an Unknown Input Observer (UIO).The proposed UIO design guarantees robust residual generation through decoupling the disturbances effects from the faults ones. The discrimination between the faults and the effects of uncertain signals and perturbations on the residues minimizes the duration of fault detection for deterministic systems. Then these results were extended to the general case of stochastic linear systems by using an optimal observers for systems with unknown disturbances and noise. A simulation is done on an aeronautic model to illustrate the theoretical development. © 2014 IEEE. |
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). @article{Aribi20143679b,
title = {Fault detection based on fractional order models: Application to diagnosis of thermal systems},
author = {Asma Aribi and Christophe Farges and Mohamed Aoun and Pierre Melchior and Slaheddine Najar and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84900012609\&doi=10.1016%2fj.cnsns.2014.03.006\&partnerID=40\&md5=aaff38cb40225b2d869c6016e9b2e011},
doi = {10.1016/j.cnsns.2014.03.006},
year = {2014},
date = {2014-01-01},
journal = {Communications in Nonlinear Science and Numerical Simulation},
volume = {19},
number = {10},
pages = {3679 \textendash 3693},
abstract = {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.},
note = {Cited by: 28},
keywords = {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},
pubstate = {published},
tppubtype = {article}
}
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. |
Houiji, Marwa; Hamdaoui, Rim; Aoun, Mohamed Detection time for deterministic and stochastic systems with unknown inputs Conférence 2014, (Cited by: 1). @conference{Houiji2014,
title = {Detection time for deterministic and stochastic systems with unknown inputs},
author = {Marwa Houiji and Rim Hamdaoui and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946686815\&doi=10.1109%2fCISTEM.2014.7076982\&partnerID=40\&md5=0be64cd709ae198f91a4d2b9aecc2dae},
doi = {10.1109/CISTEM.2014.7076982},
year = {2014},
date = {2014-01-01},
journal = {2014 International Conference on Electrical Sciences and Technologies in Maghreb, CISTEM 2014},
abstract = {This paper investigates the detection and diagnosis of actuator faults by using an Unknown Input Observer (UIO).The proposed UIO design guarantees robust residual generation through decoupling the disturbances effects from the faults ones. The discrimination between the faults and the effects of uncertain signals and perturbations on the residues minimizes the duration of fault detection for deterministic systems. Then these results were extended to the general case of stochastic linear systems by using an optimal observers for systems with unknown disturbances and noise. A simulation is done on an aeronautic model to illustrate the theoretical development. © 2014 IEEE.},
note = {Cited by: 1},
keywords = {Detection and diagnosis, Deterministic systems, Fault detection, Linear systems, Optimal observers, Robust residuals, Stochastic linear systems, Stochastic systems, Theoretical development, Unknown disturbance, Unknown input observer},
pubstate = {published},
tppubtype = {conference}
}
This paper investigates the detection and diagnosis of actuator faults by using an Unknown Input Observer (UIO).The proposed UIO design guarantees robust residual generation through decoupling the disturbances effects from the faults ones. The discrimination between the faults and the effects of uncertain signals and perturbations on the residues minimizes the duration of fault detection for deterministic systems. Then these results were extended to the general case of stochastic linear systems by using an optimal observers for systems with unknown disturbances and noise. A simulation is done on an aeronautic model to illustrate the theoretical development. © 2014 IEEE. |
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). @article{Aribi20143679,
title = {Fault detection based on fractional order models: Application to diagnosis of thermal systems},
author = {Asma Aribi and Christophe Farges and Mohamed Aoun and Pierre Melchior and Slaheddine Najar and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84900012609\&doi=10.1016%2fj.cnsns.2014.03.006\&partnerID=40\&md5=aaff38cb40225b2d869c6016e9b2e011},
doi = {10.1016/j.cnsns.2014.03.006},
year = {2014},
date = {2014-01-01},
journal = {Communications in Nonlinear Science and Numerical Simulation},
volume = {19},
number = {10},
pages = {3679 \textendash 3693},
abstract = {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.},
note = {Cited by: 28},
keywords = {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},
pubstate = {published},
tppubtype = {article}
}
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. |
2011
|
Aoun, Mohamed; Aribi, Asma; Najar, Slaheddine; Abdelkrim, Mohamed Naceur On the fractional systems’ fault detection: A comparison between fractional and rational residual sensitivity Conférence 2011, (Cited by: 8). @conference{Aoun2011f,
title = {On the fractional systems' fault detection: A comparison between fractional and rational residual sensitivity},
author = {Mohamed Aoun and Asma Aribi and Slaheddine Najar and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79957903547\&doi=10.1109%2fSSD.2011.5767424\&partnerID=40\&md5=2e22d74f672e2ae986db94c4dbcd72e6},
doi = {10.1109/SSD.2011.5767424},
year = {2011},
date = {2011-01-01},
journal = {International Multi-Conference on Systems, Signals and Devices, SSD'11 - Summary Proceedings},
abstract = {This paper shows the interest of extending the dynamic parity space fault detection method for fractional systems. Accordingly, a comparison between fractional and rational residual generators using the later method is presented. An analysis of fractional and rational residuals' sensitivity shows the merits of the fractional residual generators. A numerical example illustrating the advantage of using fractional residual generators for fractional systems diagnosis is given. © 2011 IEEE.},
note = {Cited by: 8},
keywords = {Detection methods, Fault detection, fault diagnosis, Fractional derivatives, Fractional systems, Numerical example, Parity spaces, Residual generator, residual sensitivity, Signal detection},
pubstate = {published},
tppubtype = {conference}
}
This paper shows the interest of extending the dynamic parity space fault detection method for fractional systems. Accordingly, a comparison between fractional and rational residual generators using the later method is presented. An analysis of fractional and rational residuals’ sensitivity shows the merits of the fractional residual generators. A numerical example illustrating the advantage of using fractional residual generators for fractional systems diagnosis is given. © 2011 IEEE. |
