Modeling and Real-Time Stabilization of an Aircraft Having Eight Rotors



We introduce an original configuration of a multi rotor helicopter composed of eight rotors. Four rotors, also called main rotors, are used to stabilize the attitude of the helicopter, while the four extra rotors (lateral rotors) are used to perform the lateral movements of the unmanned aerial vehicle (UAV). The main characteristic of this configuration is that the attitude and translation dynamics are decoupled. The dynamic model is obtained using the well known Euler–Lagrange approach. To validate the model, we performed real-time experiments using a simple nonlinear control law using optical flow and image processing.


Modeling Control UAV Multirotors 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bouguet, J.Y.: Pyramidal implementation of the Lucas Kanade feature tracker. In: Technical report Intel Corporation (1999)Google Scholar
  2. 2.
    Lyon, D.: A military perspective on small unmanned aerial vehicles. Instrumentation and Measurement Magazine, IEEE, 7(3), 27–31 (2004)CrossRefGoogle Scholar
  3. 3.
    Salazar-Cruz, S., Lozano, R.: Stabilization and nonlinear control for a novel tri-rotor mini-aircraft. In: Proc. of IEEE International Conference on Robotics and Automation, pp. 2924–2929 (2005)Google Scholar
  4. 4.
    Green, W.E., Oh, P.Y., Barrows, G.L.: Flying insect inspired vision for autonomous aerial robot maneuvers in near-earth environments. In: Proc. of IEEE International Conference on Robotics and Automation (2004)Google Scholar
  5. 5.
    Romero, H., Benosman, R., Lozano, R.: Stabilization and location of a four rotors helicopter applying vision. In Proc. American Control Conference ACC. pp. 3931–3936 (2006)Google Scholar
  6. 6.
    Castillo, P., Lozano, R., Dzul, A.: Stabilization of a mini rotorcraft with four rotors. Control Systems Magazine, IEEE 25, 45–55 (2005)CrossRefMathSciNetGoogle Scholar
  7. 7.
    Tayebi, A., McGilvray, S.: Attitude stabilization of a four-rotor aerial robot. In: Proc. of Conference on Decision and Control, IEEE CDC., vol. 2, pp. 1216–1221 (2004)Google Scholar
  8. 8.
    Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd Edn. In: Cambridge University Press, ISBN 0521540518 (2004)Google Scholar
  9. 9.
    McCormick Jr., B.W.: Aerodynamics of V/STOL Flight. Dover Publication Inc. (1999)Google Scholar
  10. 10.
    Beauchemin, S.S., Barron, J.L.: The computation of optical flow. In: ACM Computing Surveys, 27, 433–467 (1995)CrossRefGoogle Scholar
  11. 11.
    King, C.Y.: Virtual instrumentation-based system in a real-time applications of GPS/GIS. In: Proc. Conference on Recent Advances in Space Technologies, pp. 403–408 (2003)Google Scholar
  12. 12.
    Sasiadek, J.Z., Hartana, P.: Sensor Fusion for Navigation of an Autonomous Unmanned Aerial Vehicle. In: Proc. International Conference on Robotics and Automation, vol. 4, pp. 429–434 (2004)Google Scholar
  13. 13.
    Yoo, C.-S., Ahn, I.-K.: Low cost GPS/INS sensor fusion system for UAV navigation. In: Proc. Digital Avionics Systems Conference, vol. 2, pp. 8.A.1-1–8.A.1-9 (2003)Google Scholar
  14. 14.
    Goldstein, H.: Classical Mechanics, 2nd Edn. Addison Wesley Series in Physics, Adison-Wesley, U.S.A. (1980)Google Scholar
  15. 15.
    Castillo, P., Lozano, R., Dzul, A.: Modelling and Control of Mini-Flying Machines. Springer-Verlag in Advances in Industrial Control. ISBN: 1-85233-957-8 (2005) JulyGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • S. Salazar
    • 1
  • H. Romero
    • 2
    • 3
  • R. Lozano
    • 2
    • 3
  • P. Castillo
    • 2
    • 3
  1. 1.Instituto de Investigaciones EléctricasCuernavacaMexico
  2. 2.Heudiasyc UMR 6599 CNRS-UTCCompiègneFrance
  3. 3.LAFMIA UMR 3175 CNRS-CINVESTAVMexico D.F.Mexico

Personalised recommendations