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A hybrid frequency-time domain technique for ground effect identification

Published online by Cambridge University Press:  03 February 2016

A. Vitale ,
N. Genito ,
L. Garbarino ,
U. Ciniglio  and
F. Corraro
A. Vitale
Affiliation:
a.vitale@cira.it, CIRA, Italian Aerospace Research Centre, Capua, Italy
N. Genito
Affiliation:
a.vitale@cira.it, CIRA, Italian Aerospace Research Centre, Capua, Italy
L. Garbarino
Affiliation:
a.vitale@cira.it, CIRA, Italian Aerospace Research Centre, Capua, Italy
U. Ciniglio
Affiliation:
a.vitale@cira.it, CIRA, Italian Aerospace Research Centre, Capua, Italy
F. Corraro
Affiliation:
a.vitale@cira.it, CIRA, Italian Aerospace Research Centre, Capua, Italy
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Abstract

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The estimation from flight data of aerodynamic parameters for vehicle in steady-state conditions, perturbed by an identification manoeuvre, is a well-established technology, whereas system identification from dynamic flight data is a subject of continuous interest. This paper presents a hybrid frequency and time domain technique for identification of vehicle longitudinal aerodynamic model, including the ground effect. Identification is performed in the framework of a multi-step approach, in which, first aerodynamic coefficients are estimated in the frequency domain, using an equation error method; then time domain techniques are applied to identify out of ground effect aerodynamic derivatives and ground effect model parameters. The technique was successfully applied to flight data of an experimental ultra light aircraft. Identification results showed that the proposed method works properly also in the dynamic phases of the flight or when no dedicated identification manoeuvres are executed. Moreover, the identified longitudinal aerodynamic model was used to design the flight control system that successfully performed many autonomous landings.

Information

Type
Research Article
Information
The Aeronautical Journal , Volume 114 , Issue 1156 , June 2010 , pp. 377 - 385
Copyright
Copyright © Royal Aeronautical Society 2010 

References

1. Morelli, E.A., Real-time parameter estimation in the frequency domain, J Guidance, Control and Dynamic, September–October 2000, 23, (5), pp 812–818.Google Scholar
2. Jategaonkar, R.V., Flight vehicle system identification: A time domain methodology, AIAA Progress in Aeronautics and Astronautics, 2006, 216, AIAA, Reston, VA, USA.Google Scholar
3. Curry, R.E., Dynamic ground effect for a cranked arrow wing airplane, 1997, NASA Technical Memorandum 4799, Edwards, CA, USA.Google Scholar
4. Corda, S., Stephenson, M.T., Burcham, F.W and Curry, R.E., Dynamic ground effects flight test of an F-15 aircraft, 1994, NASA Technical Memorandum 4604, Edwards, CA, USA.Google Scholar
5. Devesa, B., Jourdan, C. and Marc, C., Ground-effect identification and autoland system validation from flight data, J Aircr, July–August 2004, 41, (4), pp 730–734.Google Scholar
6. Rohlf, D., Global model approach for X-31 VECTOR system identification, J Aircr, January–February 2005, 42, (1), pp 54–62.Google Scholar
7. Emslie, K., Garner, H.C., Jupp, J.A. and Wedderspoon, J.R., Low-speed longitudinal aerodynamic characteristics of aircraft in ground effect, 1972, ESDU No 72023.Google Scholar
8. Ahmed, M.R., Takasaki, T and Kohama, Y., Aerodynamics of a NACA4412 airfoil in ground effect, AIAA J, January 2007, 45, (1), pp 37–47.Google Scholar
9. Lee, P.H., Lan, C.E. and Muirheadt, V.U., Experimental investigation of dynamic ground effect, J Aircr, June 1989, 26, (6), pp 497–498.Google Scholar
10. Hoff, J.C. and Cook, M.V., Aircraft parameter identification using an estimation-before-modelling technique, Aeronaut J, August-September 1996, 100, (997), pp 259–268.Google Scholar
11. Vitale, A., Corraro, F., Bernard, M. and De Matteis, G., Unscented Kalman filtering for reentry vehicle identification in the transonic regime, J Aircr, September-October 2009, 46, (5), pp 164–1659.Google Scholar
12. Maine, R.E and Iliff, K.W., Application of parameter estimation to aircraft stability and control, June 1986, NASA Reference Publication 1168.Google Scholar
13. Di Vito, V., De Lellis, E., Corraro, F., Genito, N., Marrone, C. and Ciniglio, U., UAV free path safe DGPS/AHRS autolanding: Algorithm and flight tests, June 2008, UAV SYSTEM 2008 — International Technical Conference & Exhibition, Paris, France.Google Scholar
14. McCormic, B.W., Aerodynamics, aeronautics and flight mechanics, 1995, John Wiley and Sons, New York, USA.Google Scholar