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