Vincent Sircoulomb, Ghaleb Hoblos, Houcine Chafouk, and José Ragot
[1] B.D. Anderson & J.B. Moore, Optimal filtering (EnglewoodCliffs, NJ: Prentice Hall, USA, 1979). [2] K.L. Shi, T.F. Chan, Y.K. Wang, & S.L. Ho, Speed estimationof an induction motor drive using an optimized extendedKalman filter, IEEE Transactions on Industrial Electronics,49 (1), Berlin, Germany, 2002, 124–133. [3] V. Sircoulomb, G. Hoblos, & H. Chafouk, A fault tolerantKalman filter bank, International Journal of AMSE, Rouen,2005, 99–108. [4] D. Simon & D.L. Simon, Kalman filtering with inequalityconstraints for turbofan health estimation, IEE Proceedings onControl Theory and Applications, 153 (3), 2006, 371–378. [5] S. Rezaei & R. Sengupta, Kalman filter based integration ofDGPS and vehicle sensors for localization, IEEE Transactionson Control System Technology, 15 (6), 2007, 1080–1088. [6] S.G. Kim, J.L. Crassidis, Y. Cheng, & A.M. Fosbury, Kalmanfiltering for relative spacecraft attitude and position estimation,Journal of Guidance, Control and Dynamics, 30 (1), 2007,133–143. [7] C.S. Johns & J. Mandel, A two-stage ensemble Kalman filterfor smooth data assimilation, Environmental and EcologicalStatistics, 15 (1), 2007, 101–110. [8] N. Gupta, Constrained Kalman filtering and predicting be-haviour in agent-based financial market models, Doctoral Dis-sertation, University of Oxford, UK, 2008. [9] C.K. Chui & G. Chen, Kalman filtering with real-time appli-cations (Springer-Verlag, 2008). [10] E. Mazzour & D. Hodouin, Une aide algorithmique `al’optimisation du placement des capteurs dans un proc´ed´e,Journal Europ´een des Syst`emes Automatis´es, 37 (10), 2003,1251–1276. [11] G. Hoblos, M. Staroswiecki, & A. A¨ıtouche, Optimal designof fault tolerant sensor network, IEEE Conference on Controland Applications, Anchorage, Alaska, USA, 2000, 467–472. [12] M. Staroswiecki, G. Hoblos, & A. A¨ıtouche, Sensor networkdesign for fault tolerant estimation, International Journal ofAdaptive Control and Signal Processing, 18 (1), 2004, 55–72. [13] N.E. Wu, S. Thavamani, Y. Zhang, & M. Blanke, Sensor faultmasking of a ship propulsion system, Control Engineering andPractice, 14 (11), 2006, 1337–1345. [14] T.L. Chen & R.Z. You, A novel fault-tolerant system for sensordrift compensation, Sensors and Actuators A, 147 (2), 2008,623–632. [15] S. Li & G. Tao, Feedback based adaptive compensation ofcontrol system sensor uncertainties, Automatica, 45 (2), 2009,393–404. [16] D. Maquin, M. Luong, & J. Ragot, Fault detection and isolationand sensor network design, Journal Europ´een des Syst`emesAutomatis´es, 31, 1997, 393–406. [17] Y. Yan, Sensor placement and diagnosability analysis at de-sign stage, IMonet Workshop on Model-based Systems,16th European Conference on Artificial Intelligence, Valencia,Spain, 2004. [18] A. Rosich, R. Sarrate, V. Puig, & T. Escobet, Efficient optimalsensor placement for model-based FDI using an incrementalalgorithm, IEEE Conference on Decision and Control, NewOrleans, LA, USA, 2007, 2590–2595. [19] M. Bagajewicz, Design and upgrade of process plant instru-mentation (Lancaster, USA: Technomic Publishers, 2000). [20] M. Staroswiecki, G. Hoblos, & A. A¨ıtouche, Fault toleranceanalysis of sensor systems, 38th IEEE Conference on Decisionand Control, Phoenix, Arizona, USA, 1999, 3581–3586. [21] D.L. Aspach & H.W. Sorenson, Nonlinear Bayesian estimationusing Gaussian sum approximation, IEEE Transactions onAutomatic Control, 17 (4), 1972, 439–448. [22] S.J. Julier, J.K. Uhlmann, & H.F. Durrant-White, A newmethod for nonlinear transformation of means and covariancesin filters and estimators, IEEE Transactions on AutomaticControl, 45 (3), 2000, 477–482. [23] M. Nφrgaard, N.K. Poulsen, & O. Ravn, New developmentsin state estimation for nonlinear systems, Automatica, 36 (11),2000, 1627–1638. [24] K. Ito & K. Xiong, Gaussian filters for nonlinear filteringproblems, IEEE Transactions on Automatic Control, 45 (5),2000, 910–927. [25] G. Evensen, Data assimilation: The ensemble Kalman filter(Berlin, Germany: Springer-Verlag, 2006). [26] A. Doucet, N. de Freitas, & N. Gordon, Sequential MonteCarlo methods in practice (New York, USA: Springer-Verlag,2001). [27] R. Van der Merwe, Sigma-point Kalman filters for probabilisticinference in dynamic state-space models, Doctoral Dissertation,Faculty of the OGI School of Science & Engineering, Oregon,USA, 2004. [28] V. Sircoulomb, G. Hoblos, H. Chafouk, & J. Ragot, Evaluationof estimation quality with respect to sensors losses, 7th QualitaWorld Congress, Tanger, Morocco, 2007. [29] N.E. Wu, K. Zhou, & G. Salomon, On reconfigurability, IFACSafeprocess, Budapest, Hungary, 2000, 846–851. [30] M. Staroswiecki, On reconfigurability with respect to sensorfailures, IFAC World Congress, Barcelona, Spain, 2002. [31] V. Sircoulomb, G. Hoblos, H. Chafouk, & J. Ragot, Analyseet synth`ese de redondance de capteurs en vue d’am´eliorerl’estimation d’´etat d’un syst`eme, Colloque Interdisciplinaireen Instrumentation, Nancy, France, 2007, 141–148. [32] V. Sircoulomb, Etude des concepts de filtrage robusteaux m´econnaissances de mod`ele et aux pertes de mesures.Application aux syst`emes de navigation, Doctoral Dissertation,Institut National Polytechnique de Lorraine, Nancy, France,2008. [33] S. Orderud, Comparison of Kalman filter estimation approachesfor state space models with nonlinear measurements, Scandi-navian Conference on Simulation and Modeling, Trondheim,Norway, 2005. [34] V. Sircoulomb, G. Hoblos, H. Chafouk, & J. Ragot, Analy-sis and comparison of nonlinear filtering methods, AdvancedControl and Diagnosis Workshop, Nancy, France, 2006. [35] J. LaViola, A comparison of unscented and extended Kalmanfilter for estimating a quaternion motion, American ControlConference, Denver, Colorado, USA, 2003, 2435–2440.
Important Links:
Go Back