http://iet.metastore.ingenta.com
1887

Model predictive quadrotor control: attitude, altitude and position experimental studies

Model predictive quadrotor control: attitude, altitude and position experimental studies

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Control Theory & Applications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This study addresses the control problem of an unmanned quadrotor in an indoor environment where there is lack of absolute localisation data. Based on an attached inertia measurement unit, a sonar and an optic-flow sensor, the state vector is estimated using sensor fusion algorithms. A novel switching model predictive controller is designed in order to achieve precise trajectory control, under the presence of forcible wind gusts. The quadrotor’s attitude, altitude and horizontal linearised dynamics result in a set of piecewise affine models, enabling the controller to account for a larger part of the quadrotor’s flight envelope while modelling the effects of atmospheric disturbances as additive-affine terms in the system. The proposed controller algorithm accounts for the state and actuation constraints of the system. The controller is implemented on a quadrotor prototype in indoor position tracking, hovering and attitude manoeuvres experiments. The experimental results indicate the overall system’s efficiency in position/altitude/attitude set-point manoeuvres.

References

    1. 1)
      • Ryan, A., Hedrick, J.: `A mode-switching path planner for UAV-assisted search and rescue', 44thIEEE Conf. Decision and Control, 2005 European Control Conf., CDC-ECC ’05, 2005, Seville, Spain, p. 1471–1476.
    2. 2)
      • Alexis, K., Nikolakopoulos, G., Tzes, A., Dritsas, L.: `Coordination of helicopter UAVs for aerial forest-fire surveillance', Applications of intelligent control to engineering systems, 2009, Springer, The Netherlands, p. 169–193.
    3. 3)
      • Sarris, Z.: `Survey of UAV applications in civil markets', Mediterranean Conf. on Control and Automation, 2001, Ancona, Italy.
    4. 4)
    5. 5)
    6. 6)
      • (2005) Autonomous vehicles in support of naval operations.
    7. 7)
      • Gray, S.: `Cooperation between UAVs in search and destroy mission', American Institute of Aeronautics and Astronautics (AIAA) Guidance, Navigation, and Control Conf. and Exhibit, 2003, Austin, USA.
    8. 8)
      • Girard, A., Howell, A., Hedrick, J.: `Border patrol and surveillance missions using multiple unmanned air vehicles', 43rdIEEE Conf. on Decision and Control, December 2004, Atlantis, Paradise Island, Bahamas, p. 620–625, vol. 1.
    9. 9)
      • Murphy, D., Cycon, J.: `Applications for mini VTOL UAV for law enforcement', Information and Training Technologies for Law Enforcement, November 1998, Boston, MA, USA.
    10. 10)
      • Bouabdallah, S., Noth, A., Siegwart, R.: `PID vs LQ control techniques applied to an indoor micro quadrotor', Proc. 2004 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 2004, (IROS 2004), 2004, p. 2451–2456, vol. 3.
    11. 11)
      • K. Alexis , G. Nikolakopoulos , A. Tzes . Autonomous quadrotor position and attitude PID/PIDD control in GPS-denied environments. Int. Rev. Autom. Control , 421 - 430
    12. 12)
      • Hoffmann, G.M., Huang, H., Waslander, S.L., Tomlin, C.J.: `Quadrotor helicopter flight dynamics and control: theory and experiment', Proc. Guidance, Navigation, and Control Conf., 2007.
    13. 13)
      • Benallegue, A., Mokhtari, A., Fridman, L.: `Feedback linearization and high order sliding mode observer for a quadrotor UAV', Int. Workshop Variable Structure Systems (VSS’06), 2006, Alghero, Sardinia, p. 365–372.
    14. 14)
      • Bouabdallah, S., Siegwart, R.: `Full control of a quadrotor', IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 2007, IROS 2007, 2007, San Diego, CA, USA, p. 153–158.
    15. 15)
    16. 16)
    17. 17)
    18. 18)
    19. 19)
      • Alexis, K., Nikolakopoulos, G., Tzes, A.: `Design and experimental verification of a constrained finite time optimal control scheme for the attitude control of a quadrotor helicopter subject to wind gusts', 2010 Int. Conf. on Robotics and Automation, 2010, Anchorage, AK, USA, p. 1636–1641.
    20. 20)
      • Alexis, K., Nikolakopoulos, G., Tzes, A.: `Constrained optimal attitude control of a quadrotor helicopter subject to wind-gusts: experimental studies', American Control Conf. '10, 2010, Baltimore, USA, p. 4451–4455.
    21. 21)
    22. 22)
      • Costelo, M.F.: `A theory of the analysis of rotorcraft operation in atmospheric turbulence', 1992, PhD, Georgia Institute of Technology, School of Aerospace Engineering.
    23. 23)
      • Yang, X., Pota, H., Garrat, M.: `Design of a gust-attenuation controller for landing operations of unmanned autonomous helicopters', 18thIEEE Int. Conf. on Control Applications, July 2009, Saint Petersburg, Russia, p. 1300–1305.
    24. 24)
    25. 25)
    26. 26)
      • E.F. Camacho , C. Bordons . (2004) Model predictive control.
    27. 27)
      • Bouabdallah, S.: `Design and control of quadrotors with application to autonomous flying', 2007, PhD, EPFL, Lausanee, STI School of Engineering.
    28. 28)
      • Xsens: ‘Xsens MTi-G’, http://www.xsens.com/en/general/mti-g, 2008.
    29. 29)
      • Centeye: ‘Tam2 and Tam4 vision chips’, http://centeye.com/technology/vision-chips, WA, USA, February 2011.
    30. 30)
    31. 31)
      • J.-C. Zufferey . (2008) Bio-inspired flying robots – experimental synthesis of autonomous indoor flyers.
    32. 32)
      • D. Simon . (2006) Optimal state estimation: Kalman, H infinity and nonlinear approaches.
    33. 33)
      • Lange, S., Sunderhauf, N., Protzel, P.: `A vision based onboard approach for landing and position control of an autonomous multirotor UAV in GPS-denied environments', International Conference on Advanced Robotics (ICAR), Munich Marriot Hotel, June 2009, Germany, p. 22–24..
    34. 34)
      • R.E. Moore . (1979) Methods and applications of interval analysis.
    35. 35)
    36. 36)
      • Abraham, R.H., Bachrach, Roy N.: `Autonomous flight in unstructured and unkown indoor environments', European Micro Aerial Vehicle Conf. and Flight Competition (EMAV), ASTI, D-CIS LAB, TUDelft, 14–17 September 2009, THALES, The Netherlands.
    37. 37)
      • Huang, H.: `Aerodynamics and control of autonomous quadrotor helicopters in aggressive maneuvering', Int. Conf. on Robotics and Automation, 2009, Kobe, Japan.
    38. 38)
      • B. Mettler . (2003) Identification modeling and characteristics of miniature rotorcraft.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cta.2011.0348
Loading

Related content

content/journals/10.1049/iet-cta.2011.0348
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address