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Analysis of a reversible flight control system response to atmospheric turbulence

Published online by Cambridge University Press:  03 February 2016

K. Raissi ,
M. Mani ,
H. Ghaffari  and
A. Nobari
K. Raissi
Affiliation:
Department of Aerospace Engineering and Center for Excellence in Computational Aerospace Engineering, Amirkabir University of Technology, Tehran, Iran
M. Mani
Affiliation:
Department of Aerospace Engineering and Center for Excellence in Computational Aerospace Engineering, Amirkabir University of Technology, Tehran, Iran
H. Ghaffari
Affiliation:
Department of Aerospace Engineering and Center for Excellence in Computational Aerospace Engineering, Amirkabir University of Technology, Tehran, Iran
A. Nobari
Affiliation:
Department of Aerospace Engineering and Center for Excellence in Computational Aerospace Engineering, Amirkabir University of Technology, Tehran, Iran
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Abstract

A mathematical model was developed for the reversible longitudinal control system of a regional commuter aircraft using the available geometry, mass property and kinematics. The model was incorporated into a general multi-body dynamics code and validated using existing manufacturer’s data as well as recorded data from several flights. Analysis of the flight data revealed light atmosphere turbulence level. To investigate the effect of higher turbulence intensity on the reversible flight control system, a sever turbulence level was generated using Von Karman model for the same flight level and velocity. The result was used as a random input to the dynamic model for computation of the frequency response of control column. It was shown that turbulence could act as a random input through the hinge moment during the flight and introduced a new mode in the lower end of power spectral density curve. The energy induced by this low frequency input resulted in large displacement of control column in simulation which surpassed the existing limits. Therefore it should be taken into account when dealing with handling quality as well as autopilot design.

Type
Research Article
Information
The Aeronautical Journal , Volume 112 , Issue 1128 , February 2008 , pp. 93 - 100
Copyright
Copyright © Royal Aeronautical Society 2008 

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References

1. Hiltner, D.W., An evaluation of an analytical simulation of an airplane with tailplane icing by comparison to flight data, 2000, NASA/CR-2000-210561, Glen Research Center, Ohio.Google Scholar
2. Weiss, S., Gockel, W., Monnich, W. and Rohlf, D., Identification of Dornier-328 reversible flight control system, 1998, AIAA Modeling and Simulation Technology Conference, Boston, MA, August 1998.Google Scholar
3. Godin, F.R., Aircraft flight control system modelling — cable construction kit, 2000, International ADAMS User Conference, Orlando, Florida, 19-21 June 2000.Google Scholar
4. Roskam, J., Airplane flight dynamics and automatic flight control, 1998, Roskam Aviation Corporation, Ottawa, Kansas.Google Scholar
5. Cornman, L.B., Meymaris, G. and Limber, M., An update on the FAA aviation weather research program’s in situ turbulence measurement and reporting system, 2004, National Center for Atmospheric Research, Boulder, Colorado, US.Google Scholar
6. Goodman, H.R., Over-all loads and buffeting measurements, 1948, Air Force — NACA Conference, Muroc Air Force Base, CA.Google Scholar
7. Sadoff, M. and Sisk, T., Stall characteristics obtained from Flight 10 of Northrop X-4 No 2 airplane, 1950, NACA Research Memorandum, Washington.Google Scholar
8. ANON Federal Aviation Regulation 25.207, 2001, Federal Aviation Administration, Washington.Google Scholar
9. Sharma, V.K., P-3 Aircraft buffet response characterization, 2001, 39th Aerospace Science Meeting and Exhibition, Reno, NV, January 2001.Google Scholar
10. Ranaudo, R.J., Ratvsaky, T.P. and Van Zante, J.F., Flying qualities evaluation of a commuter aircraft with an ice contaminated tailplane, 2000, SAE General Aviation Technology Conference, Wichita, KS.Google Scholar
11. Jategaonkar, R., Flight vehicle system identification, AIAA Progress in Astronautics and Aeronautics, 2006, 216, Reston, VA.Google Scholar
12. Wei-Xin, R., Gang, C. and Wei-Hua, H., Empirical formulas to estimate cable tension by cable fundamental frequency, Structural Engineering and Mech, 2005, 20, (3), pp 363–380.Google Scholar
13. Park, J., ADAMS Modeling technique for mechanical control cables, 2001 ADAMS User Conference at Novi Hilton, Michigan, USA.Google Scholar
14. Roskam, J., Airplane Design Handbook, Roskam Aviation Corporation, Ottawa, Kansas, 1979.Google Scholar
15. Check, K.C., Hu, H. and Loh, N.K., Modeling and identification of a class of servomechanism systems with stick-slip friction, J Dynamic Systems, Measurement and Control, 1988, 110, pp 324–328.Google Scholar
16. Burgermeister, B., Arnold, M. and Esterl, B., DAE time integration for real-time applications in multi-body dynamics, J Applied Mathematics and Mech, 2006, 86, (10), pp 759–771, Wiley-VCH Verlag, Weinheim.Google Scholar
17. Bertogalli, V., Bittanti, S. and Lovera, M., Simulation and identification of helicopter rotor dynamics using a general-purpose multi-body code, J of The Franklin Institute, 1999, 336, pp 783–797.Google Scholar
18. ANON Boeing design manual — mechanical control — cable friction, 1978, Boeing Co.Google Scholar
19. ANON General specification for wire rope, flexible, for aircraft control, April 2005, MIL-DTL-83420M.Google Scholar
20. Slagowski, S. and Potter, A., Using ADAMS to model cable driven hyper-redundant flexible manipulators, 2000 International ADAMS User Conference.Google Scholar
21. Elliott, A.S., Efficient modeling of extensible cables and pulley systems in ADAMS, 2002 European ADAMS Users Conference.Google Scholar
22. ANON. Modeling and simulating process, 2002, ADAMS/Solver Documentation.Google Scholar