DocumentCode :
658023
Title :
Doubly fed induction generator fault diagnosis using unknown input Takagi-Sugeno observer
Author :
Ouyessaad, H. ; Chafouk, Houcine ; Lefebvre, Dimitri
Author_Institution :
IRSEEM - ESIGELEC, St. Etienne du Rouvray, France
fYear :
2013
fDate :
6-8 May 2013
Firstpage :
530
Lastpage :
535
Abstract :
This paper presents a new approach to detect and isolate the current sensor faults, a doubly fed induction generator (DFIG) for a wind turbine application. A method using an unknown input of multiple observers described via Takagi-Sugeno (T-S) multiple models. A bank of multiple observers generates a set of residuals for detection and isolation of sensor faults which can affect a TS model. The stability and the performance of the multiple models are formulated in terms of Linear Matrix Inequalities (LMIs). The LMIs can be efficiently solved using convex optimization techniques, where the convergence conditions of the state estimation errors are expressed in LMI formulation using the Lyapunov method.
Keywords :
Lyapunov methods; convergence; convex programming; fault diagnosis; fuzzy set theory; induction motors; linear matrix inequalities; observers; stability; wind turbines; DFIG; LMIs; Lyapunov method; convergence conditions; convex optimization techniques; current sensor fault detection; current sensor fault isolation; doubly fed induction generator fault diagnosis; linear matrix inequalities; stability; state estimation errors; unknown input Takagi-Sugeno observer; wind turbine; Generators; Mathematical model; Observers; Rotors; Stators; Vectors; Wind turbines; Current sensor Fault; Fault Diagnosis; Multiple Observer; Takagi-Sugeno Multiple models; Wind Turbine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Decision and Information Technologies (CoDIT), 2013 International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4673-5547-6
Type :
conf
DOI :
10.1109/CoDIT.2013.6689600
Filename :
6689600
Link To Document :
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