期刊文献+

Aircraft Flutter Modal Parameter Identification Using a Numerically Robust Least-squares Estimator in Frequency Domain 被引量:5

原文传递
导出
摘要 Recently,frequency-based least-squares(LS)estimators have found wide application in identifying aircraft flutter parameters.However,the frequency methods are often known to suffer from numerical difficulties when identifying a continuous-time model,especially,of broader frequency or higher order.In this article,a numerically robust LS estimator based on vector orthogonal polynomial is proposed to solve the numerical problem of multivariable systems and applied to the flutter testing.The key idea of this method is to represent the frequency response function(FRF)matrix by a right matrix fraction description(RMFD)model,and expand the numerator and denominator polynomial matrices on a vector orthogonal basis.As a result,a perfect numerical condition(numerical condition equals 1)can be obtained for linear LS estimator.Finally,this method is verified by flutter test of a wing model in a wind tunnel and real flight flutter test of an aircraft.The results are compared to those with notably LMS PolyMAX,which is not troubled by the numerical problem as it is established in z domain(e.g.derived from a discrete-time model).The verification has evidenced that this method,apart from overcoming the numerical problem,yields the results comparable to those acquired with LMS PolyMAX,or even considerably better at some frequency bands.
机构地区 College of Automation
出处 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2008年第6期550-558,共9页 中国航空学报(英文版)
基金 Aeronautical Science Foundation of China(2007ZD53053) NPU Foundation for Fundamental Research(NPU-FFR-W018104)
  • 相关文献

参考文献18

  • 1Wright J R. Flight flutter testing, lecture series on flutter of winged aircraft. Belgium: Von Karman Institute, 1991.
  • 2Brenner M J, Lind R C, Voracek D F. Overview of recent flight flutter testing research at NASA Dryden. NASA CR 4792, 1997.
  • 3Kehoe W M. A historical overview of flight flutter testing. NASA CR 4720, 1995.
  • 4Cooper J E. Parameter estimation methods for flight flutter testing. Proceedings of the 80th AGARD Structures and Materials Panel, AGARD CP-566. 1995.
  • 5Verboven P, Cauberghe B, Guillaume P, et al. Modal parameter estimation and monitoring for on-line flight flutter analysis. Mechanical Systems and Signal Processing 2004; 18(3): 587-610.
  • 6Pintelon R, Kollar I. On the frequency scaling in continuous-time modeling. IEEE Transactions on Instrumentation and Measurement 2005; 54(1): 318-321.
  • 7Pintelon R, Schoukens J. System identification: a frequency domain approach. Los Alamitos: IEEE Press, 2001.
  • 8Rolain Y, Pintelon R, Xu K Q, et al. On the use of orthogonal polynomials in high order frequency domain system identification and its application to modal parameter estimation. Proceedings of the 33rd IEEE Conference on Decision and Control. 1994; 3365-3373.
  • 9Bultheel A, van Barel M, Rolain Y, et al. Robust rational approximation for identification. Proceedings of the 40th IEEE Conference on Decision and Control. 2001; 4770- 4775.
  • 10van Barel M, Bultheel A. A parallel algorithm for discrete least squares rational approximation. Numerische Mathematik 1992; 63(1): 99-121.

同被引文献22

  • 1曾议,竺长安,沈连婠,齐继阳.基于群智能算法的设备布局离散优化研究[J].计算机集成制造系统,2007,13(3):541-547. 被引量:11
  • 2Richardson M H, Formenti D L. Parameter estimation from frequency response measurements using rational fraction polynomials[C]//Proceedings of the 1st International Modal Analysis Conference. 1982: 167-181.
  • 3Verboven P, Guillaume P, Cauberghe B, et al. Modal parameter estimation from input-output Fourier data using frequency-domain maximum likelihood identification[J]. Journal of Sound and Vibration, 2004, 276(3) :957-979.
  • 4Van der Auweraer H, Guillaume P, Verboven P, et al. Application of a fast stabilizing frequency domain parameter estimation method[J]. Journal of Dynamic System, Measurement, and Control, 2001, 123(4): 651-659.
  • 5Zhang L M, Kanda H. Some applications of frequency do main polyreference modal parameter identification[C]// Proceedings of the 4th International Modal Analysis Conference. 1986:1237 -1245.
  • 6Cauberghe B, Guillaume P, Verboven P, et al. On the in fluence of the parameter constraint on the stability of poles [J]. Mechanical Systems and Signal Processing, 2005, 19 (5) : 989-1014.
  • 7Rolain Y, Pintelon R, Xu K Q, et al. On the use of orthogonal polynomials in high order frequency domain system identification and its application to modal parameter estimation[C]//Proceedings of the 33rd IEEE Conference on Decision and Control. 1994: 3365-3373.
  • 8Rolain Y, Pintelon R, Xu K Q, et al. Best conditioned parametric identification of transfer function models in the frequency domain [J]. IEEE Transactions on Automatic Control, 1995, 40 (11): 1954-1960.
  • 9Chen K F, Jiao Q Y, Shen Y H. On the frequency mapping of modal parameters identification[J]. Mechanical Systems and Signal Processing, 2007, 21(4) : 1665-1673.
  • 10Allemang R J, Brown D L. A unified matrix polynomial approach to modal identification[J]. Journal of Sound and Vibration, 1998, 211(3): 301-322.

引证文献5

二级引证文献22

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部