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Model–Based Techniques for Virtual Sensing of Longitudinal Flight Parameters

International Journal of Applied Mathematics and Computer Science's Cover Image
International Journal of Applied Mathematics and Computer Science
Safety, Fault Diagnosis and Fault Tolerant Control in Aerospace Systems, Silvio Simani, Paolo Castaldi (Eds.)

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Arulampalam, S., Maskell, S. and Gordon, N. (2002). A tutorial on particle filters for on-line non-linear/non-Gaussian Bayesian tracking, IEEE Transactions on Signal Processing 50(2): 174-188.10.1109/78.978374Search in Google Scholar

Boiffier, J.-L. (1998). The Dynamics of Flight: The Equations, John Wiley & Sons, Chichester.Search in Google Scholar

Bucharles, A., Cumer, C., Hardier, G., Jacquier, B., Janot, A., Le Moing, T., Seren, C., Toussaint, C. and Vacher, P. (2012). An overview of relevant issues for aircraft model identification, ONERA, AerospaceLab Journal (4): 13-33.Search in Google Scholar

Chang, C.T. and Chen, J.W. (1995). Implementation issues concerning the EKF-based fault diagnosis techniques, Chemical Engineering Science 50(18): 2861-2882.10.1016/0009-2509(95)00127-QSearch in Google Scholar

Chen, R. and Liu, J.S. (2000). Mixture Kalman filters, Journal of the Royal Statistical Society 62(3): 493-508.10.1111/1467-9868.00246Search in Google Scholar

Chen, S., Hong, X., Harris, C.J. and Sharkey, P.M. (2004). Sparse modelling using orthogonal forward regression with PRESS statistic and regularization, IEEE Transactions on Systems, Man and Cybernetics 34(2): 898-911.10.1109/TSMCB.2003.817107Search in Google Scholar

Chen, S., Hong, X., Luk, B.L. and Harris, C.J. (2009). Non-linear system identification using particle swarm optimization tuned radial basis function models, International Journal of Bio-Inspired Computation 1(4): 246-258.10.1504/IJBIC.2009.024723Search in Google Scholar

Clerc, M. (2006). Particle Swarm Optimization, ISTE, London.10.1002/9780470612163Search in Google Scholar

Davies, M. (2003). The Standard Handbook for Aeronautical and Astronautical Engineers, McGraw-Hill, New York, NY.Search in Google Scholar

De Freitas, N. (2002). Rao-Blackwellised particle filtering for fault diagnosis, Proceedings of the IEEE Aerospace Conference, Big Sky, MT, USA, pp. 1767-1772.Search in Google Scholar

Dennis, J.E. and Schnabel, R.B. (1996). Numerical Methods for Unconstrained Optimization and Nonlinear Equations, SIAM, Philadelphia, PA.10.1137/1.9781611971200Search in Google Scholar

Frank, P.M. (1996). Analytical and qualitative model-based fault diagnosis: A survey and some new results, European Journal of Control 2(1): 6-28.10.1016/S0947-3580(96)70024-9Search in Google Scholar

Garcia, E.A. and Frank, P.M. (1997). Deterministic nonlinear observer-based approaches to fault diagnoses: A survey, Control Engineering Practice 5(5): 663-670.10.1016/S0967-0661(97)00048-8Search in Google Scholar

Ghanbarpour Asl, H. and Pourtakdoust, S.H. (2007). UD covariance factorization for unscented Kalman filter using sequential measurements update, World Academy of Science, Engineering and Technology (34): 368-376.Search in Google Scholar

Goupil, P. (2010). Oscillatory failure case detection in the A380 electrical flight control system by analytical redundancy, Control Engineering Practice 18(9): 1110-1119.10.1016/j.conengprac.2009.04.003Search in Google Scholar

Goupil, P. (2011). Airbus state of the art and practices on FDI and FTC in flight control system, Control Engineering Practice 19(6): 524-539.10.1016/j.conengprac.2010.12.009Search in Google Scholar

Hanlon, P.D. and Maybeck, P.S. (2000). Multiple-model adaptive estimation using a residual correlation Kalman filter bank, IEEE Transactions on Aerospace and Electronic Systems 36(2): 393-406.10.1109/7.845216Search in Google Scholar

Hardier, G. (1998). Recurrent RBF networks for suspension system modeling and wear diagnosis of a damper, Proceedings of the IEEE World Congress on Computational Intelligence, Anchorage, AK, USA, Vol. 3, pp. 2441-2446. Search in Google Scholar

Hardier, G., Roos, C. and Seren, C. (2013). Creating sparse rational approximations for linear fractional representations using surrogate modeling, Proceedings of the 3rd International Conference on Intelligent Control and Automation Science, Chengdu, China, pp. 238-243.Search in Google Scholar

Hardier, G. and Seren, C. (2013). Aerodynamic model inversion for virtual sensing of longitudinal flight parameters, Proceedings of the 2nd International Conference on Control and Fault Tolerant Systems, Nice, France, pp. 140-145.Search in Google Scholar

Isermann, R. (2008). Model-based fault-detection and diagnosis: Status and applications, Annual Reviews in Control 29(1): 71-85.10.1016/j.arcontrol.2004.12.002Search in Google Scholar

Jategaonkar, R.V. (2006). Flight Vehicle System Identification: A Time Domain Methodology, F.K. Lu Edition, AIAA, Inc., Arlington, VA.10.2514/4.866852Search in Google Scholar

Julier, S.J. and Uhlmann, J.K. (2004). Unscented filtering and nonlinear estimation, Proceedings of the IEEE 92(3): 401-422.10.1109/JPROC.2003.823141Search in Google Scholar

Kavuri, S.N., Venkatasubramanian, V., Rengaswamy, R. and Yin, K. (2003). A review of process fault detection and diagnosis, Computers and Chemical Engineering 27(3): 293-346.10.1016/S0098-1354(02)00162-XSearch in Google Scholar

Kay, S.M. and Marple, S.L. (1981). Spectrum analysis-A modern perspective, Proceedings of the IEEE 10.1109/PROC.1981.12184Search in Google Scholar

Lu, S., Cai, L., Ding, L. and Chen, J. (2007). Two efficient implementation forms of unscented Kalman filter, Proceedings of the IEEE International Conference on Control and Automation, Guangzhou, China, pp. 761-764.Search in Google Scholar

Marzat, J., Piet-Lahanier, H., Damongeot, F. and Walter, E. (2012). Model-based fault diagnosis for aerospace systems: A survey, Journal of Aerospace Engineering 226(10): 1329-1360.10.1177/0954410011421717Search in Google Scholar

Morelli, E.A. and DeLoach, R. (2003). Wind tunnel database development using modern experiment design and multivariate orthogonal functions, Proceedings of the 41st AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, USA, AIAA 2003-653.10.2514/6.2003-653Search in Google Scholar

Nelles, O. and Isermann, R. (1996). Basis function networks for interpolation of local linear models, Proceedings of the 35th IEEE International Conference on Decision and Control, Kobe, Japan, pp. 470-475.Search in Google Scholar

Oosterom, M. and Babuska, R. (2000). Virtual sensor for FDI in flight control systems-fuzzy modeling approach, Proceedings of the 39th IEEE Conference on Decision and Control, Sydney, Australia, pp. 2645-2650.Search in Google Scholar

Patton, R.J. and Chen, J. (1994). A review of parity space approaches to fault diagnosis for aerospace systems, Journal of Guidance, Control and Dynamics 17(2): 278-285.10.2514/3.21194Search in Google Scholar

Ru, J. and Li, R. (2003). Interacting multiple model algorithm with maximum likelihood estimation for FDI, Proceedings of the IEEE International Symposium on Intelligent control, Houston, TX, USA, pp. 661-666.Search in Google Scholar

Samara, P.A., Fouskitakis, G.N., Sakellariou, J.S. and Fassois, S.D. (2008). A statistical method for the detection of sensor abrupt faults in aircraft control systems, IEEE Transactions on Control Systems Technology 16(4): 789-798.10.1109/TCST.2007.903109Search in Google Scholar

Seren, C. and Hardier, G. (2013). Adaptive extended Kalman filtering for virtual sensing of longitudinal flight parameters, Proceedings of the 2nd International Conference on Control and Fault Tolerant Systems, Nice, France, pp. 25-30.Search in Google Scholar

Seren, C., Hardier, G. and Ezerzere, P. (2011). On-line estimation of longitudinal flight parameters, Proceedings of the SAE AeroTech Congress and Exhibition, Toulouse, France.10.4271/2011-01-2769Search in Google Scholar

Smidl, V. and Peroutka, Z. (2012). Advantages of square-root extended Kalman filter for sensorless control of AC drives, IEEE Transactions on Industrial Electronics 59(11): 4189-4196. 10.1109/TIE.2011.2180273Search in Google Scholar

Traverse, P., Lacaze, I. and Souryis, J. (2004). Airbus fly-by-wire: A total approach to dependability, Proceedings of the 18th IFIP World Computer Congress, Toulouse, France, pp. 191-212.Search in Google Scholar

Van der Merwe, R. and Wan, E. (2001). Efficient derivative free Kalman filters, Proceedings of the 9th European Symposium on Artificial Neural Networks, Bruges, Belgium, pp. 205-210.Search in Google Scholar

Zolghadri, A. (2012). Advanced model-based FDIR techniques for aerospace systems: Today challenges and opportunities, Progress in Aerospace Sciences 53: 18-29. 10.1016/j.paerosci.2012.02.004Search in Google Scholar

eISSN:
2083-8492
Sprache:
Englisch
Zeitrahmen der Veröffentlichung:
4 Hefte pro Jahr
Fachgebiete der Zeitschrift:
Mathematik, Angewandte Mathematik