References
- Bisplinghoff, R.L., & Ashley, H. (1962). Principles of aeroelasticity. Mineola, NY: Dover Publications.
- Björk, Å. (1996). Numerical methods for least squares problems. Philadelphia, PA: SIAM.
- Blom, R.S., & Van den Hof, P.M.J. (2010). Multivariable frequency domain identification using IV-based linear regression. In Proceedings of the IEEE Conference on Decision and Control. Atlanta, GA.
- Bracewell, R.N. (1999). The Fourier transform and its applications. New York, NY: McGraw-Hill.
- Brenner, M.J., Lind, R.C., & Voracek, D.F. (1997). Overview of recent flight flutter testing research at NASA sryden (Technical memorandum 4792). Edwards, CA: NASA Dryden Flight Research Center.
- Cauberghe, B. (2004). Applied frequency-domain system identification in the field of experimental and operational modal analysis. Brussels: Vrije Universiteit.
- Correa, G.O., & Glover, K. (1984). Pseudo-canonical forms, identifiable parametrizations and simple parameter estimation for linear multivariable systems : Input-output models. Automatica, 20, 429–442.
- David, B. (2001). Parameter estimation in nonlinear dynamical systems with correlated noise Louvain-La-Neuve: Université Catholique de Louvain.
- De Callafon, R., De Roover, D., & Van Den Hof, P. (1996). Multivariable least squares frequency domain identification using polynomial matrix fraction descriptions. In Proceedings of the IEEE Conference on Decision and Control. Kobe, Japan.
- Garnier, H., Gilson, M., Young, P., & Huselstein, E. (2007). An optimal IV technique for identifying continuous-time transfer function model of multiple input systems. Control Engineering Practice, 15, 471–486.
- Garnier, H., & Wang, L. (2008). Identification of continuous-time models from sampled data. Berlin: Springer-Verlag.
- Garrick, I.E., & Reed, W.H. III. (1981). Historical development of aircraft flutter. Journal of Aircraft, 18, 897–912.
- Gevers, M., & Wertz, V. (1987). Parametrization issues in system identification. In Proceedings of the IFAC World Congress. Munich, Germany.
- Gillberg, J. (2006). Frequency domain identification of continuous-time systems. Linköping: University of Linköping.
- Glover, K., & Willems, J.C. (1974). Parametrizations of linear dynamical systems: Canonical forms and identifiability. IEEE Transactions on Automatic Control, 19, 640–645.
- Golub, G.H., & Van Loan, C.F. (1996). Matrix computations. Baltimore, MA: Johns Hopkins University Press.
- Guidorzi, R.P., & Beghelli, S. (1982). Input-output multistructural models in multivariable systems identification. In Proceedings of the IFAC Symposium on Identification and System Parameter Estimation. Washington, D.C.
- Guillaume, P., & Pintelon, R. (1996). A Gauss-Newton-like optimization algorithm for ‘weighted’ nonlinear least-squares problems. Transactions on Signal Processing, 44, 2222–2228.
- Guillaume, P., Verboven, P., Vanlanduit, S., Van Der Auweraer, H., & Peeters, B. (2003). A poly-reference implementation of the least-squares complex frequency-domain estimator. In Proceedings of the International Modal Analysis Conference. Kissimmee, FL.
- Hermans, L., & Van der Auweraer, H. (1999). Modal testing and analysis of structures under operational conditions: Industrial applications. Mechanical Systems and Signal Processing, 13, 193–216.
- Kailath, T. (1980). Linear systems. Upper Saddle River, NJ: Prentice Hall.
- Kehoe, M.W. (1995). A historical preview of flight flutter testing. In Proceedings of the AGARD Conference on Structures and Materials Pane. Rotterdam, the Netherlands.
- Klein, V., & Morelli, E.A. (2006). Aircraft system identification. Reston, VA: AIAA.
- Labarrère, M., Krief, J.P., & Gimonet, B. (1978). Le filtrage et ses applications. Toulouse: Cepadues Editions.
- Ljung, L. (1999). System identification: Theory for the user. Upper Saddle River, NJ: Prentice Hall.
- Mathews, J.H., & Fink, K.D. (2004). Numerical methods using Matlab. Upper Saddle River, NJ: Prentice Hall.
- McKelvey, T., & Helmersson, A. (1997). System identification using an over-parametrized model class–Improving the optimization algorithm. In Proceedings of the IEEE Conference on Decision and Control. San Diego, CA.
- Miller, D.N., De Callafon, R.A., & Brenner, M.J. (2012). Covariance-based realization algorithm for the identification of aeroelastic dynamics. Journal of Guidance Control and Dynamics, 35, 1169–1177.
- Minoux, M. (1983). Programmation mathématique. Théorie et algorithmes. Paris: Dunod.
- Nissim, E., & Gilyard, G.B. (1989). Methods for experimental determination of flutter speed by parameter identification (Technical report, NASA TP/2923). Washington, D.C.: NASA.
- Phillips, A.W., & Allemang, R.J. (2005). Data presentation schemes for selection and identification of modal parameters. In Proceedings of the International Modal Analysis Conference. Orlando, FL.
- Pintelon, R., Guillaume, P., Rolain, Y., Schoukens, J., & Van Hamme, H. (1994). Parametric identification of transfer functions in the frequency domain - A survey. IEEE Transactions on Automatic Control, 39, 2245–2259.
- Pintelon, R., & Schoukens, J. (2001). System identification: A frequency domain approach. New York, NY: IEEE Press.
- Pintelon, R., Schoukens, J., & Vandersteen, G. (1997). Frequency domain system identification using arbitrary signals. IEEE Transactions on Automatic Control, 42, 1717–1720.
- Roger, K.L. (1977). Airplane math modeling methods for active control design. In Proceedings of the AGARD Conference. Lisbon, Portugal.
- Sanathanan, C.K., & Koerner, J. (1963). Transfer function synthesis as a ratio of two complex plynomials. IEEE Transactions on Automatic Control, 9, 56–58.
- Söderström, T., & Stoica, P.G. (1983). Instrumental variable methods for system identification. New York, NY: Springer.
- Söderström, T., & Stoica, P.G. (1989). System identification. Upper Saddle River, NJ: Prentice Hall.
- Solo, V. (1980). Some aspects of recursive parameter estimation. International Journal of Control, 32, 395–410.
- Steiglitz, K., & McBride, L.E. (1965). A technique for the identification of linear systems. IEEE Transactions on Automatic Control, 10, 461–464.
- Süli, E., & Mayers, D. (2003). An introduction to numerical analysis. Cambridge: Cambridge University Press.
- Uhl, T., Petko, M., Peeters, B., & Van der Auweraer, H. (2007). Embedded system for real flight flutter detection. In Proceedings of the International Workshop on Structural Health Monitoring. Stanford University, CA.
- Vacher, P., & Bucharles, A. (2006). A multi-sensor parametric identification procedure in the frequency domain for the real-time surveillance of flutter. In Proceedings of the IFAC Symposium on System Identification. Newcastle, Australia.
- Vacher, P., Jacquier, B., & Bucharles, A. (2009). Flutter flight tests: A challenging benchmark for real-time methods. In Proceedings of the International Workshop on Sequential Methodologies IWSM 2009. Troyes, France.
- Vacher, P., Jacquier, B., & Bucharles, A. (2010). Extensions of the MAC criterion to complex modes. In Proceedings of the International Conference on Noise and Vibration Engineering. Leuven, Belgium.
- Vacher, P., Jacquier, B., & Bucharles, A. (2011). Design of linear input combinations for improved modal analysis of MIMO systems. In Proceedings of the Journées Identification Modélisation Expérimentale. Douai, France.
- Van Den Hof, P., & Douma, S.G. (2008). An IV-based iterative linear regression algorithm with optimal output error properties (DCSC Technical report, 09-018). Delft: Delft University of Technology
- Van den Hof, P.M.J., Sippe, G., Douma, S.G., & Toth, R. (2008). An IV-based iterative linear regression algorithm with optimal output error properties (DCSC technical report nr. 09-018). Delft: Delft University of Technology.
- Van Overbeek, A.J.M., & Ljung, L. (1982). On-line structure selection for multivariable state-space models. Automatica, 18, 529–543.
- Vayssettes, J., Vacher, P., & Mercère, G. (2012). An iterative algorithm for modal analysis based on structured matrix fractions. In Proceedings of the IFAC Symposium on System Identification. Brussels, Belgium.
- Welch, P.D. (1967). The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms. IEEE Transactions on Audio and Electroacoustics, 15, 70–73.
- Whitfield, A.H. (1987). Asymptotic behaviour of transfer function synthesis methods. International Journal of Control, 45, 1083–1092.
- Young, P.C. (1976). Some observations on instrumental variable methods of time-series analysis. International Journal of Control, 23, 593–612.
- Young, P.C. (1998). Data-based mechanistic modelling of engineering systems. Journal of Vibration and Control, 4, 5–28.
- Young, P.C. (2011). Recursive estimation and time-series analysis: An introduction for the student and practitioner. New York, NY: Springer.
- Young, P.C., Garnier, H., & Gilson, M. (2008). Refined instrumental variable identification of continuous-time hybrid Box–Jenkins models. In H. Garnier & L. Wang (Eds.), Identification of Continuous-Time Models from Sampled Data (pp. 91–131). New York, NY: Springer.
- Young, P.C., & Jakeman, A.J. (1980). Refined instrumental variable methods of recursive time-series analysis Part III. Extensions. International Journal of Control, 31, 741–764.