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Aerotecnica Missili & Spazio

, Volume 93, Issue 3–4, pp 75–82 | Cite as

A methodology for the identification of inertial properties of small size UAVs

  • F. Schettini
  • E. Denti
  • G. Di Rito
  • R. Galatolo
Article

Abstract

This paper illustrates a procedure for estimating the inertial properties of small size aerial vehicles. An identification algorithm has been developed that, starting from experimental data, estimates the parameters of a physical model describing the pendular motion of a generic rigid body. The attitude time histories of a structure (“cage”), carrying the object whose inertial properties have to be evaluated, are the experimental data obtained through a measurement unit attached to the cage itself. The cage, designed in order to facilitate the assembly issues, is put in pendular motion thanks to a needle shaped pivot, placed to the cage top and leaning against a beam. Before proceeding to the identification of the aerial vehicle inertial properties, several tests have been performed to evaluate the performance of the algorithm. A preliminary effectiveness of the algorithm has been assessed via simulation environment, by artificially creating “virtual” time histories. Afterwards, the algorithm has been validated experimentally by loading the cage with a proof mass of known inertial characteristics. During these experimental tests, specific attention has been focused on the effect of the cage initial attitude on the inertial properties estimate. After this algorithm test phase, the developed methodology has been applied to a small rotary-wing UAV in order to evaluate its inertial properties.

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References

  1. 1.
    R. V. Jategaonkar, “Flight Vehicle System Identification: A Time Domain Methodology”, AIAA — Progess in Astronautics and Aeronautics, ISBN 978-1563478369, 2006.Google Scholar
  2. 2.
    M. D. McEwen, “Dynamic System Identification and Modeling of a Rotary Wing UAV for Stability and Control Analysis”, Ph.D. Thesis, Naval Postgraduate School, Monterey, CA, USA, 1998.Google Scholar
  3. 3.
    C. L. Bottasso, F. Luraghi, G. Maisano, “Time-Domain Parameter Estimation for First-Principle Rotorcraft Models using Recursive and Batch Procedures: Formulation and Preliminary Results”, Scientific Report DIA-SR 09-05, 2009.Google Scholar
  4. 4.
    P. G. Hamel, V. Jategaonkar, “The Role of system identification for flight vehicle applications” — revisited in Proceeding of System Identification for Integrated Aircraft Development and Flight Testing — RTO SCI Symposium, Madrid, Spain, 1998.Google Scholar
  5. 5.
    C. L. Bottasso, D. Leonello, A. Maffezzoli, F. Riccardi, “A procedure for the identification of the inertial properties of small-size UAVs” in Proceeding of XX AIDAA Congress, Milan, Italy, 2009.Google Scholar
  6. 6.
    M. R. Jardin, E. R. Mueller, “Optimized measurements of UAV mass moment of inertia with a bifilar pendulum” in Proceeding of AIAA Guidance, Navigation and Control Conference and Exhibit, Hilton Head, SC, USA, 2007.CrossRefGoogle Scholar
  7. 7.
    C. Doniselli, M. Gobbi, G. Mastinu, “Measuring the inertia tensor of vehicles”, Vehicle System Dynamics Supplement, Vol.37, pp. 301–313, 2002.CrossRefGoogle Scholar
  8. 8.
    A. Fregolent, A. Sestieri, “Identification of rigid body inertia properties from experimental frequency response”, Journal of Mechanical Systems and Signal Processing, Vol.10, pp. 697–709, 1996.CrossRefGoogle Scholar
  9. 9.
    A. Gentile, L. Mangialardi, G. Mantriota, A. Trentadue, “Measurement of the inertia tensor: an experimental proposal”, Journal of Measurement, Vol.16, pp. 241–254, 1995.CrossRefGoogle Scholar

Copyright information

© AIDAA Associazione Italiana di Aeronautica e Astronautica 2014

Authors and Affiliations

  • F. Schettini
    • 1
  • E. Denti
    • 1
  • G. Di Rito
    • 1
  • R. Galatolo
    • 1
  1. 1.Department of Civil and Industrial Engineering - Aerospace DivisionUniversity of PisaPisaItaly

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