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Identification of a Cessna Citation II Model Based on Flight Test Data

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Advances in Aerospace Guidance, Navigation and Control

Abstract

A new high-fidelity Cessna II simulation model is developed that is valid throughout the normal, pre-stall flight envelope. From an extensive collection of flight test data, aerodynamic model identification was performed using the Two-Step Method. New in this approach is the use of the Unscented Kalman Filter for an improved accuracy and robustness of the state estimation step. Also, for the first time an explicit data-driven model structure selection is presented for the Citation II by making use of an orthogonal regression scheme. This procedure has indicated that most of the six non-dimensional forces and moments can be parametrized sufficiently by a linear model structure. It was shown that only the translational and lateral aerodynamic force models would benefit from the addition of higher order terms, more specifically the squared angle of attack and angle of sideslip. The newly identified aerodynamic model was implemented into an upgraded version of the existing simulation framework and will serve as a basis for the integration of a stall and post-stall model.

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References

  1. Federal Aviation Administration, Qualification, Service, and Use of Crewmembers and Aircraft Dispatchers, Technical Report, Department of Transportation, US, 2013

    Google Scholar 

  2. van der Linden CAAM (1998) DASMAT - Delft University Aircraft Simulation Model and Analysis Tool. Delft University Press, Delft

    Google Scholar 

  3. Mulder JA, Baarspul M, Breeman JH, Nieuwpoort AMH, Verbaak JPF, Steeman PSJM (1987) Determination of the Mathematical Model for the New Dutch Government Civil Aviation Flying School Flight Simulator, Society of Flight Test Engineers, 18th Annual Symposium. Delft University of Technology, Amsterdam

    Google Scholar 

  4. Oliveira J, Chu QP, Mulder JA, Balini HMNK, Vos WGM (2005) Output error method and two step method for aerodynamic model identification. In: AIAA Guidance, Navigation, and Control Conference and Exhibit, pp 1–9, August, 2005

    Google Scholar 

  5. Nahi NE (1969) Estimation Theory and Applications. John Wiley and Sons, New York

    MATH  Google Scholar 

  6. Mulder JA, Chu QP, Sridhar JK, Breeman JH, Laban M (1999) Non-linear aircraft flight path reconstruction review and new advances. Prog Aerosp Sci 35(7):673–726

    Article  Google Scholar 

  7. Mulder JA, Sridhar JK, Breeman JH (1994) Identification of Dynamic Systems- Applications to Aircraft Part 2: Nonlinear Analysis and Manoeuvre Design, vol 3. North Atlantic Treaty Organisation, Neuilly Sur Seine

    Google Scholar 

  8. Julier SJ, Uhlmann JK (1997) A New Extension of the Kalman Filter to Nonlinear Systems. International Symposium for Aerospace Defense Sensing Simulutation and Controls 3(2):26

    Google Scholar 

  9. Cessna Aircraft Company (1990) Operating Manual Model 550 Citation II, Unit -0627 And On. Technical Report, Wichita, Kansas, USA

    Google Scholar 

  10. Laban M (1994) On-Line Aircraft Aerodynamic Model Identification, Ph.d. thesis, Delft University of Technology, Delft

    Google Scholar 

  11. de Visser CC (2011) Global Nonlinear Model Identification with Multivariate Splines, Ph.D. thesis, Delft University of Technology, Delft

    Google Scholar 

  12. Mulder M, Lubbers B, Zaal PMT, van Paassen MM, Mulder JA (2009) Aerodynamic hinge moment coefficient estimation using automatic fly-by-wire control inputs. In: Proceedings of the AIAA modeling and simulation technologies conference and exhibit, chicago (IL), No 2, pp 2009–5692

    Google Scholar 

  13. Chowdhary G, Jategaonkar R (2010) Aerodynamic parameter estimation from flight data applying extended and unscented Kalman filter. Aerosp Sci Technol 14(2):106–117

    Article  Google Scholar 

  14. Julier SJ, Uhlmann JK (2004) Unscented filtering and nonlinear estimation. Proc IEEE 92(3):401–422

    Article  Google Scholar 

  15. Wan EA, Van Der Merwe R (2000) The unscented kalman filter for nonlinear estimation, adaptive systems for signal processing, communications, and control symposium 2000. AS-SPCC IEEE 2002:153–158

    Google Scholar 

  16. Van Der Merwe R, Wan EA (2001) The square-root unscented Kalman filter for state and parameter-estimation. In: Proceedings. (ICASSP ’01). 2001 IEEE international conference on acoustics, speech, and signal processing, vol 6, pp 3461–3464

    Google Scholar 

  17. van der Merwe R, Wan EA (2004) Sigma-Point Kalman Filters for integrated navigation. In: Proceedings of the 60th annual meeting of the institute of navigation (ION), pp 641–654

    Google Scholar 

  18. Sibley G, Sukhatme GS, Matthies LH (2006) The Iterated Sigma Point Kalman Filter with Applications to Long Range Stereo, Rss

    Google Scholar 

  19. Armesto L, Tornero J, Vincze M (2008) On multi-rate fusion for non-linear sampled-data systems: Application to a 6D tracking system. Robot Auton Syst 56(8):706–715

    Article  Google Scholar 

  20. Klein V (1989) Estimation of aircraft aerodynamic parameters from flight data. Prog Aerosp Sci 26(1):1–77

    Article  Google Scholar 

  21. Morelli EA (1998) Global nonlinear parametric modelling with application to F-16 aerodynamics. In: Proceedings of the american control conference, vol 2, pp 997–1001

    Google Scholar 

  22. Morelli E, Derry SD (2005) Aerodynamic parameter estimation for the X-43A (Hyper-X) from flight data. In: AIAA atmosperic flightmechanics conference and exhibit, August 2005

    Google Scholar 

  23. Goldberg MA, Cho HA (2003) Introduction to Regression Analysis. WIT Press, Southampton, UK

    Google Scholar 

  24. Watson PK, Teelucksingh SS (2002) A Practical Introduction to Econometric Methods: Classical and Modern. University of the West Indies Press

    Google Scholar 

  25. Morelli EA (2006) Practical aspects of the equation-error method for aircraft parameter estimation. AIAA Atmos Flight Mech Conf 6114:1–18

    Google Scholar 

  26. Batterson JG, Klein V (1989) Partitioning of flight data for aerodynamic modeling of aircraft at high angles of attack. J Aircr 26(4):334–339

    Article  Google Scholar 

  27. Klein V, Batterson JG, Murphy PC (1981) Determination of Airplane Model Structure from Fflight Data by Using Modified Stepwise Regression. Technical Report, NASA Langley Research Center, Hampton

    Google Scholar 

  28. Lombaerts T, Oort EV, Chu QP, Mulder JA, Joosten D (2010) Online aerodynamic model structure selection and parameter estimation for fault tolerant control. J Guid Control Dyn 33(3):707–723

    Article  Google Scholar 

  29. Morelli E (2012) Efficient global aerodynamic modeling from flight data. In: 50th AIAA aerospace sciences meeting including the new horizons forum and aerospace exposition. aerospace sciences meetings, american institute of aeronautics and astronautics Jan 2012

    Google Scholar 

  30. Grauer JA, Morelli EA (2014) Generic global aerodynamic model for aircraft. J Aircr 52(1):13–20

    Google Scholar 

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Correspondence to M. A. van den Hoek .

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van den Hoek, M.A., de Visser, C.C., Pool, D.M. (2018). Identification of a Cessna Citation II Model Based on Flight Test Data. In: Dołęga, B., Głębocki, R., Kordos, D., Żugaj, M. (eds) Advances in Aerospace Guidance, Navigation and Control. Springer, Cham. https://doi.org/10.1007/978-3-319-65283-2_14

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  • DOI: https://doi.org/10.1007/978-3-319-65283-2_14

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  • Online ISBN: 978-3-319-65283-2

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