The current paper presents a method to identify and estimate gross errors for linear dynamic systems using polynomial approximation. The method presented in a previous paper which uses linear dynamic reconciliation, is extended to allow the dynamic estimation of errors. This method is applied to the doubly fed induction generator (DFIG) of a wind turbine. The technique is validated on an experimental system used to emulate the working of the wind turbine.
NarasimhanS.JordacheC.Data reconciliation and gross error detection - an intelligent use of process data, 2000 (Gulf Publishing Company, Houston, Texas).
2.
VaclaveckV.Studies on system engineering III. Optimal choice of the balance measurements in complicated chemical systemsChem. Engng Sci., 1969, 24, 947.
3.
MahR. S. H.StanleyG. M.DowningD. W.Reconciliation and rectification of process flow and inventory dataInd. Engng Chem. Process Des. Dev., 1976, 15, 175–183.
4.
CroweC. M.CamposY. A. G.HrymakA.Reconciliation of process flow rates by matrix projection. I: Linear caseAIChE J., 1983, 29, 881–888.
5.
DarouachM.Observabilité et validation des données des systèmes de grande dimension, application à l'équilibrage des bilans de mesures. Thèse de doctorat d'état, Nancy, 1986.
6.
MaquinD.Observabilité, diagnostic et validation de données des procédés industriels. Thèse de l'Université de Nancy, 1987.
7.
RagotJ.DarouachM.MaquinD.BlochG.Validation de données et diagnostic, 1990 (Hermès, Paris).
8.
HeraudN.Validation et observabilité des systèmes multilinéaires. Thèse de doctorat de l'Institut National Polytechnique de Lorraine, 1991.
9.
StanleyG. M.MahR. S. H.Estimation of flows and temperatures in process networksAIChE J., 1977, 23, 642–650.
10.
DarouachM.ZasadzinskiM.Data reconciliation in generalized linear dynamic systemsAIChE J., 1991, 37, 193.
11.
KaoC. S.TamhaneA. C.MahR. S. H.Gross error detection in serially correlated process data. 2. Dynamic systemsInd. Engng Chem. Res., 1992, 31, 254.
12.
RollinsD. K.DevanathanS.Unbiased estimation in dynamic data reconciliationAIChE J., 1993, 39, 1330.
13.
RamamurthiY.SistuP. B.BequetteB. W.Control-relevant dynamic data reconciliation and parameter estimationComputers Chem. Engng, 1993, 17, 41.
14.
KarjalaT. W.HimmelblauD. M.Dynamic reconciliation of data via recurrent neural nets and the extended Kalman filterAIChE J., 1996, 42, 2225.
15.
AlbuquerqueJ. S.BieglerL. T.Data reconciliation and gross-error detection for dynamic systemsAIChE J., 1996, 42, 2841.
16.
BagajewiczM. J.JiangQ.Integral approach to plant linear dynamic reconciliationAIChE J., 1997, 43, 2546–2558.
17.
StavrouA.SeddingH.PenmannJ.Current monitoring for detecting inter-turn shorts circuits in induction motorsIEMDC'99, Seattle, USA, 1999.
18.
ThomsonW. T.On line MCSA to diagnose shorted turns in low voltage stator windings of 3-phase induction motors prior to failureIEMDC'01, Cambridge, USA, 2001.
19.
LouisJ. P.Modélisation des machines électriques en vue de leur commande: Concepts généraux, 2004, Hermès, Lavoisier.
20.
KhatounianF.MonmassonE.BerthreauF.DelaleauE.LouisJ. P.Control of a doubly fed induction generator for aircraft applicationIEEE-IECON, Roanoke, USA, 2003.
21.
PatinN.Filtrage actif appliqué à une machine asynchrone à double alimentation sur réseau autonomeJCGE 2005, Montpellier, France, 2005.
22.
BagajewiczM. J.JiangQ.Gross error modeling and detection in plant linear dynamic conciliationComputers Chem. Engng, 1998, 22, 1789–1809.
23.
CamblongH.Minimisation de l'impact des perturbations d'origine éolienne dans la génération d'électricité par des aérogénérateurs à vitesse variable. Thèse de l'ENSAM, 2003.
24.
BennounaO.HéraudN.CamblongH.RodriguezM.Diagnosis of the doubly-fed induction generator of a wind turbineWind Engng, 2005, 29 (5), 431–448.
25.
RodriguezM.AbadG.CamblongH.Experimental evaluation of high level control strategies in a variable speed wind turbineEPE'03, Toulouse, 2003.
