DocumentCode :
3467933
Title :
State and sensor faults estimation via a proportional integral observer
Author :
Khedher, Atef ; Benothman, Kamel ; Maquin, Didier ; Benrejeb, Mohamed
Author_Institution :
LARA Autom., ENIT, Tunis
fYear :
2009
fDate :
23-26 March 2009
Firstpage :
1
Lastpage :
6
Abstract :
This paper deals with the problem of fault detection and identification in noisy systems. A proportional integral observer with unknown inputs is used to reconstruct state and sensors faults. A mathematical transformation is made to conceive an augmented system, in which the initial sensor fault appear as an unknown input. The noise effect on the state and fault estimation errors is also minimized. The obtained results are then extended to nonlinear systems described by nonlinear Takagi-Sugeno models.
Keywords :
PI control; fault diagnosis; fuzzy control; nonlinear control systems; observers; state estimation; augmented system; mathematical transformation; nonlinear Takagi-Sugeno models; nonlinear systems; proportional integral observer; sensor faults estimation; state faults estimation; Actuators; Context modeling; Linear systems; Noise measurement; Nonlinear systems; Observers; Sensor systems; Signal processing; State estimation; Takagi-Sugeno model; Takagi-Sugeno; multiple model; sensor fault; state estimation; unknown input;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Signals and Devices, 2009. SSD '09. 6th International Multi-Conference on
Conference_Location :
Djerba
Print_ISBN :
978-1-4244-4345-1
Electronic_ISBN :
978-1-4244-4346-8
Type :
conf
DOI :
10.1109/SSD.2009.4956795
Filename :
4956795
Link To Document :
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