Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter

Regular Papers Control Applications

Abstract

This paper presents two types of nonlinear controllers for an autonomous quadrotor helicopter. One type, a feedback linearization controller involves high-order derivative terms and turns out to be quite sensitive to sensor noise as well as modeling uncertainty. The second type involves a new approach to an adaptive sliding mode controller using input augmentation in order to account for the underactuated property of the helicopter, sensor noise, and uncertainty without using control inputs of large magnitude. The sliding mode controller performs very well under noisy conditions, and adaptation can effectively estimate uncertainty such as ground effects.

Keywords

Feedback linearization sliding mode control UAV quadrotor helicopter 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    S. Bouabdallah, P. Murrireri, and R. Siegwart, “Design and control of an indoor micro quadrotor,” Proc. of the IEEE International Conference on Robotics and Automation, pp. 4393–4398, 2004.Google Scholar
  2. [2]
    B. Bluteau, R. Briand, and O. Patrouix, “Design and control of an outdoor autonomous quadrotor powered by a four strokes RC engine,” Proc. of IEEE Industrial Electronics, the 32nd Annual Conference, pp. 4136–4141, 2006.Google Scholar
  3. [3]
    E. Altug, J. P. Ostrowski, and R. Mahony, “Control of a quadrotor helocopter using visual feedback,” Proc. of the IEEE International Conference on Robotics and Automation, vol. 1, pp. 72–77. 2002.Google Scholar
  4. [4]
    E. Altug, J. P. Ostrowski, and C. J. Taylor, “Quadrotor control using dual camera visual feedback,” Proc. of the IEEE International Conference on Robotics and Automation, vol. 3, pp. 4294–4299, 2003.Google Scholar
  5. [5]
    T. Madani and A. Benallegue, “Control of a quadrotor mini-helicopter via full state backstepping technique,” Proc. of the 45th IEEE Conference on Decision and Control, pp. 1515–1520, 2006.Google Scholar
  6. [6]
    T. Madani and A. Benallegue, “Backstepping sliding mode control applied to a miniature quadrotor flying robot,” Proc. of IEEE Industrial Electronics, the 32nd Annual Conference, pp. 700–705, 2006.Google Scholar
  7. [7]
    P. Castillo, P. Albertos, P. Garcia, and R. Lozano, “Simple real-time attitude stabilization of a quadrotor aircraft with bounded signals,” Proc. of the 45th IEEE Conference on Decision and Control, pp. 1533–1538, 2006.Google Scholar
  8. [8]
    N. Metni and T. Hamel, “Visual tracking control of aerial robotic systems with adaptive depth estimation,” International Journal of Control, Automation, and Systems, vol. 5, no. 1, pp. 51–60, 2007.Google Scholar
  9. [9]
    A. Benallegue, A. Mokhtari, and L. Fridman, “Feedback linearization and high order sliding mode observer for a quadrotor UAV,” Proc. of the International Workshop on Variable Structure Systems, pp. 365–372, 2006.Google Scholar
  10. [10]
    A. Tayebi and S. McGilvray, “Attitude stabilization of a VTOL quadrotor aircraft,” IEEE Trans. on Control Systems Technology, vol. 14, no. 3, pp. 562–571, 2006.CrossRefGoogle Scholar
  11. [11]
    S. Bouabdallah, A. Noth, and R. Siegwart, “PID vs LQ control techniques applied to an indoor micro quadrotor,” Proc. of the IEEE/RJS International Conference on Intelligent Robots and Systems, vol. 3, pp. 2451–2456, 2004.Google Scholar
  12. [12]
    B. Erginer and E. Altug, “Modeling and PD control of a quadrotor VTOL vehicle,” Proc. of the IEEE Intelligent Vehicles Symposium, pp. 894–899, 2007.Google Scholar
  13. [13]
    L. Besnard, Y. Shtessel, and B. Landrum, “Control of a quadrotor vehicle using sliding mode disturbance observer,” Proc. of the American Control Conference, pp. 5230–5235, 2007.Google Scholar
  14. [14]
    C. Coza and C. J. B. Macnab, “A new robust adaptive-fuzzy control method applied to quadrotor helicopter stabilization,” NAFIPS Annual meeting of the North American Fuzzy Information Society, pp. 454–458, 2006.Google Scholar
  15. [15]
    A. Mokhtari, A. Benallegue, and B. Daachi, “Robust feedback linearization and controller for a quadrotor unmanned aerial vehicle,” Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1009–1014, 2005.Google Scholar
  16. [16]
    A. Mokhtari and A. Benallegue, “Dynamic feedback controller of Euler angles and wind parameters estimation for a quadrotor unmanned aerial vehicle,” Proc. of the IEEE International Conference on Robotics and Automation, pp. 2359–2366, 2004.Google Scholar
  17. [17]
    R. Xu and U. Ozguner, “Sliding mode control of a quadrotor helicopter,” Proc. of the 45th IEEE Conference on Decision and Control, pp. 4957–4962, 2006.Google Scholar
  18. [18]
    S. Sastry, Nonlinear Systems: Analysis, Stability, and Control, Springer-Verlag, New York, NY, 1999.MATHGoogle Scholar
  19. [19]
    R. Prouty, Helicopter Performance, Stability, and Control, Krieger Pub. Co., 1995.Google Scholar

Copyright information

© The Institute of Control, Robotics and Systems Engineers and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg GmbH 2009

Authors and Affiliations

  1. 1.School of Mechanical and Aerospace Engineering and Institute of Advanced Aerospace TechnologySeoul National UniversitySeoulKorea
  2. 2.Electrical Engineering & Computer SciencesUniversity of CaliforniaBerkeleyUSA

Personalised recommendations