Skip to main content
Log in

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

  • Regular Papers
  • Control Applications
  • Published:
International Journal of Control, Automation and Systems Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  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.

  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.

  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. 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. 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.

  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.

  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.

  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. 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.

  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.

    Article  Google Scholar 

  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. 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.

  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.

  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.

  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.

  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.

  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.

  18. S. Sastry, Nonlinear Systems: Analysis, Stability, and Control, Springer-Verlag, New York, NY, 1999.

    MATH  Google Scholar 

  19. R. Prouty, Helicopter Performance, Stability, and Control, Krieger Pub. Co., 1995.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to H. Jin Kim.

Additional information

Recommended by Editorial Board member Hyo-Choong Bang under the direction of Editor Hyun Seok Yang. This work was supported by the Korea Research Foundation Grant (MOEHRD) KRF-2005-204-D00002, the Korea Science and Engineering Foundation(KOSEF) grant funded by the Korea government(MOST) R0A-2007-000-10017-0 and Engineering Research Institute at Seoul National University.

Daewon Lee received the B.S. degree in Mechanical and Aerospace Engineering from Seoul National University (SNU), Seoul, Korea, in 2005, where he is currently working toward a Ph.D. degree in Mechanical and Aerospace Engineering. He has been a member of the UAV research team at SNU since 2005. His research interests include applications of nonlinear control and vision-based control of UAV.

H. Jin Kim received the B.S. degree from Korea Advanced Institute of Technology (KAIST) in 1995, and the M.S. and Ph.D. degrees in Mechanical Engineering from University of California, Berkeley in 1999 and 2001, respectively. From 2002–2004, she was a Postdoctoral Researcher and Lecturer in Electrical Engineering and Computer Science (EECS), University of California, Berkeley (UC Berkeley). From 2004–2009, she was an Assistant Professor in the School of in Mechanical and Aerospace Engineering at Seoul National University (SNU), Seoul, Korea, where she is currently an Associate Professor. Her research interests include applications of nonlinear control theory and artificial intelligence for robotics, motion planning algorithms.

Shankar Sastry received the B.Tech. degree from the Indian Institute of Technology, Bombay, in 1977, and the M.S. degree in EECS, the M.A. degree in mathematics, and the Ph.D. degree in EECS from UC Berkeley, in 1979, 1980, and 1981, respectively. He is currently Dean of the College of Engineering at UC Berkeley. He was formerly the Director of the Center for Information Technology Research in the Interest of Society (CITRIS). He served as Chair of the EECS Department from January, 2001 through June 2004. In 2000, he served as Director of the Information Technology Office at DARPA. From 1996 to 1999, he was the Director of the Electronics Research Laboratory at Berkeley (an organized research unit on the Berkeley campus conducting research in computer sciences and all aspects of electrical engineering). He is the NEC Distinguished Professor of Electrical Engineering and Computer Sciences and holds faculty appointments in the Departments of Bioengineering, EECS and Mechanical Engineering. Prior to joining the EECS faculty in 1983 he was a Professor with the Massachusetts Institute of Technology (MIT), Cambridge. He is a member of the National Academy of Engineering and Fellow of the IEEE.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lee, D., Jin Kim, H. & Sastry, S. Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter. Int. J. Control Autom. Syst. 7, 419–428 (2009). https://doi.org/10.1007/s12555-009-0311-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12555-009-0311-8

Keywords

Navigation