Hostname: page-component-78c5997874-s2hrs Total loading time: 0 Render date: 2024-11-06T09:11:16.434Z Has data issue: false hasContentIssue false
  • English
  • Français

Frequency-domain application of Gauss-Newton method to extract aircraft longitudinal parameters

Published online by Cambridge University Press:  04 July 2016

S. C. Raisinghani  and
A. K. Goelt
S. C. Raisinghani
Affiliation:
Indian Institute of Technology, Kanpur, India
A. K. Goelt
Affiliation:
Indian Institute of Technology, Kanpur, India
Get access Rights & Permissions [Opens in a new window]

Summary

A simplified output error method based on the Gauss-Newton minimisation technique is formulated in the frequency-domain and its application demonstrated for extraction of aircraft longitudinal parameters from simulated flight data. A study is carried out to show the effects on the accuracy of estimated parameters due to use of different input forms to generate the flight data, using different initial values to start the algorithm, presence of measurment noise in the flight data and fixing some weak parameters at a priori values. It is shown that the use of Packing Theorem to increase the sparsely sampled frequency data does not lead to better accuracy by the proposed method, as has been reported for the maximum likelihood method in the literature. Finally, relative advantages of the frequency-domain approach as against the time-domain approach are pointed out by analysing the same flight data in these two domains. It is shown that frequency-domain approach is better equipped to analyse noisy-data and can yield better estimates at reduced computational time.

Type
Research Article
Information
The Aeronautical Journal , Volume 90 , Issue 891 , January 1986 , pp. 27 - 34
Copyright
Copyright © Royal Aeronautical Society 1986 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

Professor, Aeronautical Engineering Department.

†

Graduate student;now a Scientist 'B' at DRDL, Hyderabad, India.

References

1. Ekyhoff, P. Process Parameters and State Estimation. Automation, 1968, 4, 205.Google Scholar
2. Astrom, K. J. and Ekyhoff, P. System Identification — A Survey. Automatica, 1971, 7, 123.Google Scholar
3. Klein, V. Identification Evaluation Method. AGARD-LS-104, 2.1, 1979.Google Scholar
4. Gupta, N. K. New Frequency Domain Methods for System Identification. Joint Automatic Control Conference Proceedings, 1977, 2, 804.Google Scholar
5. Wells, W. R. and Keskar, D. A. Aircraft Parameter Identification in Frequency-Domain with Unsteady Aerodyna mic Modelling. Proceedings of the 5th IFAC Symposium on Identification and Systems Parameter Estimation, Darmstadt Fed Rep of Germany, September 1979.Google Scholar
6. Klein, V. Maximum Likelihood Method for Estimating Air plane Stability and Control Parameters from Flight Data in Frequency Domain, NASA TP 1637, 1980.Google Scholar
7. Raisinghani, S. C. and Adak, A. K. Aircraft Parameter Identification by Gauss-Newton Minimisation Technique Using Flight Test Data, lnt J Systems Science, December 1983, 14, 1395.Google Scholar
8. Raisinghani, S. C. and Adak, A. K. Aircraft Longitudinal Parameter Estimation by Gauss-Newton Method. J. Aero nautical Society of India, 1985, 37, No 2, 95.Google Scholar
9. Raisinghani, S. C. and Goel, A. K. Aircraft Parameter Identification by Gauss-Newton Method in Frequency-Domain. Int J Systems Science, 1985, 16, No 5, 509.Google Scholar
10. Roskam, J. Flight Dynamics of Rigid and Elastic Airplanes. Roskam Aviator and Engineering Corporation, C, 1972.Google Scholar
11. Maine, R. E. and Iliff, K. W. The Theory and Practice of Estimating the Accuracy of Dynamic Flight Determined Coeffi cients. NASA Reference Publication 1077, July 1981.Google Scholar
12. Maine, R. E. and Iliff, K. W. Formulation and Implementa tion of a Practical Algorithm for Parameter Estimation with Process and Measurement Noise. SIAM J Appl Math, December 1981, 41, No 3, 558.Google Scholar
13. Mulder, J. A. et al. Analysis of Aircraft Performance, Stability and Control. AGARD-LS-105, 5-1, 1979.Google Scholar
14. Brigham, E. O. The Fast Fourier Transform. Englewood Clifts, NJ, Prentice Hall, 1974.Google Scholar
15. Raisinghani, S. C. and Bilimoria, K. D. A new method for data pre-processing. JGCD, March-April 1984. 7, 255.Google Scholar
16. Wells, W. R. and Banda, S. S. Data Analysis for Aircraft Parameter Estimates. AIAA Atmospheric Flight Mechanics Conference, Albuquerque, New Mexico, 19th-21st August 1981.Google Scholar