Publications

@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}

}

@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}

}

@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}

}