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Journal of Intelligent & Robotic Systems

, Volume 70, Issue 1–4, pp 385–399 | Cite as

Experimental Validation of a Helicopter Autopilot Design using Model-Based PID Control

  • Bryan Godbolt
  • Nikolaos I. VitzilaiosEmail author
  • Alan F. Lynch
Article

Abstract

Autonomous helicopter flight provides a challenging control problem. In order to evaluate control designs, an experimental platform must be developed in order to conduct flight tests. However, the literature describing existing platforms focuses on the hardware details, while little information is given regarding software design and control algorithm implementation. This paper presents the design, implementation, and validation of an experimental helicopter platform with a primary focus on a software framework optimized for controller development. In order to validate the operation of this platform and provide a basis for comparison with more sophisticated nonlinear designs, a PID controller with feedforward gravity compensation is derived using the generally accepted small helicopter model and tested experimentally.

Keywords

Helicopter UAV autopilot Experimental helicopter platform Model-based control Helicopter modeling and control 

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References

  1. 1.
    Ahmed, B.: Autonomous landing of lightweight helicopters on moving platforms such as ships. Ph.D. thesis, The University of New South Wales at The Australian Defence Force Academy (2009)Google Scholar
  2. 2.
    Barczyk, M.: Nonlinear state estimation and modeling of a helicopter uav. Ph.D. thesis, Dept. of Electrical and Computer Engineering, University of Alberta, Edmonton, AB (2012)Google Scholar
  3. 3.
    Bernard, M., Kondak, K., Hommel, G.: Framework for development and test of embedded flight control software for autonomous small size helicopters. In: Embedded Systems—Modeling, Technology, and Applications, pp. 159–168. Springer (2006)Google Scholar
  4. 4.
    Bilal Ahmed, H.R.P., Garratt, M.: Flight control of a rotary wing UAV using backstepping. Int. J. Robust Nonlinear Control 20, 639–658 (2010)Google Scholar
  5. 5.
    Bisgaard, M.: Modeling, estimation, and control of helicopter slung load system. Ph.D. thesis, Aalborg University (2007)Google Scholar
  6. 6.
    Cai, G., Peng, K., Chen, B.M., Lee, T.H.: Design and assembling of a UAV helicopter system. In: International Conference on Control and Automation (ICCA2005), pp. 697–702. Budapest, Hungary (2005)Google Scholar
  7. 7.
    Castillo, P., Lozano, R., Dzul, A.E.: Modelling and Control of Mini-Flying Machines. Springer, London (2005)Google Scholar
  8. 8.
    del Cerro, J., Barrientos, A., Artieda, J., Lillo, E., Gutierez, P., Martin, R.S.: Embedded control system architecture applied to an unmanned aerial vehicle. In: IEEE International Conference on Mechatronics, pp. 254–259. Budapest (2006)Google Scholar
  9. 9.
    Farrell, J.A.: Aided Navigation: GPS with High Rate Sensors. McGraw-Hill (2008)Google Scholar
  10. 10.
    Ferruz, J., Vega, V., Ollero, A., Blanco, V.: Embedded control and development system for the HERO autonomous helicopter. In: IEEE International Conference on Mechatronics, pp. 1–6. Malaga, Spain (2009)Google Scholar
  11. 11.
    Garcia, R., Valavanis, K.: The Implementation of an Autonomous Helicopter Testbed. J. Intell. Robot. Syst. 54(1–3), 423–454 (2008)Google Scholar
  12. 12.
    Garratt, M., Ahmed, B., Pota, H.R.: Platform enhancements and system identification for control of an unmanned helicopter. In: 9th International Conference on Control, Automation, Robotics and Vision, pp. 1981–1986. Singapore (2006)Google Scholar
  13. 13.
    Gavrilets, V., Frazzoli, E., Mettler, B., Piedmonte, M., Feron, E.: Aggressive maneuvering of small autonomous helicopters: a human-centered approach. Int. J. Rob. Res. 20(10), 795–807 (2001)CrossRefGoogle Scholar
  14. 14.
    Geng, W., Huanye, S., Tiansheng, L.: Development of an embedded intelligent flight control system for the autonomously flying unmanned helicopter sky-e xplorer. In: Embedded Systems—Modeling, Technology, and Applications, pp. 121–130. Springer (2006)Google Scholar
  15. 15.
    Henzinger, T.A., Kirsch, C.M., Sanvido, M.A., Pree, W.: From control models to real-time code using Giotto. IEEE Control Syst. Mag. 23(1), 50–64 (2003)CrossRefGoogle Scholar
  16. 16.
    Johnson, E.N., Schrage, D.P.: The Georgia Tech unmanned aerial research vehicle: GTMax. In: AIAA Guidance, Navigation, and Control Conference and Exhibit. Austin, TX, USA (2003)Google Scholar
  17. 17.
    Kastelan, D.R.: Design and implementation of a GPS-aided inertial navigation system for a helicopter UAV. Master’s thesis, Dept. of Electrical and Computer Engineering, University of Alberta, Edmonton, AB (2009)Google Scholar
  18. 18.
    Kendoul, F.: Survey of Advances in Guidance, Navigation, and Control of Unmanned Rotorcraft Systems. J. Field Robot. 29, 315–378 (2012)CrossRefGoogle Scholar
  19. 19.
    Koo, T.J., Sastry, S.: Output tracking control design of a helicopter model based on approximate linearization. In: 37th IEEE Conference on Decision and Control, pp. 3635–3640. Tampa, FL (1998)Google Scholar
  20. 20.
    Mettler, B., Tischler, M.B., Kanade, T.: System identification of small-size unmanned helicopter dynamics. In: Annual Forum Proceedings-American Helicopter Society, pp. 1706–1717. Montreal, Canada (1999)Google Scholar
  21. 21.
    Mettler, B.: Identification Modeling and Characteristics of Miniature Rotorcraft. Kluwer, Norwell, MA (2003)Google Scholar
  22. 22.
    Montgomery, J.F., Johnson, A.E., Roumeliotis, S.I., Matthies, L.H.: The jet propulsion autonomous helicopter testbed: a platform for planetary exploration technology research and development. J. Field Robot. 23(3–4), 245–267 (2006)CrossRefGoogle Scholar
  23. 23.
    Murray, R.M., Li, Z., Sastry, S.S.: A Mathematical Introduction to Robotic Manipulation. CRC Press, Boca Raton, FL (1994)zbMATHGoogle Scholar
  24. 24.
    Ollero, A., Merino, L.: Control and perception techniques for aerial robotics. Annu. Rev. Control 28(2), 167–178 (2004)CrossRefGoogle Scholar
  25. 25.
    Raptis, I.A., Valavanis, K.P., Moreno, W.A.: A novel nonlinear backstepping controller design for helicopters using the rotation matrix. IEEE Trans. Control Syst. Technol. 19, 465–473 (2011)CrossRefGoogle Scholar
  26. 26.
    Raptis, I.A., Valavanis, K.P., Vachtsevanos, G.J.: Linear tracking control for small-scale unmanned helicopters. IEEE Trans. Control Syst. Technol. 20, 995–1010 (2012)CrossRefGoogle Scholar
  27. 27.
    Remuss, V., Musial, M., Deeg, C., Hommel, G.: Embedded system architecture of the second generation autonomous unmanned aerial vehicle MARVIN MARK II. In: Embedded Systems—Modeling, Technology, and Applications, pp. 101–110. Springer (2006)Google Scholar
  28. 28.
    Roberts, J.M., Corke, P.I., Buskey, G.: Low-cost flight control system for a small autonomous helicopter. In: IEEE International Conference on Robotics and Automation, pp. 546–551. Taipei, Taiwan (2003)Google Scholar
  29. 29.
    Saripalli, S., Montgomery, J.F., Sukhatme, G.S.: Visually guided landing of an unmanned aerial vehicle. IEEE Trans. Robot. Autom. 19(3), 371–380 (2003)CrossRefGoogle Scholar
  30. 30.
    Shim, D.H., Kim, H.J., Sastry, S.: Hierarchical control system synthesis for rotorcraft-based unmanned aerial vehicles. In: AIAA Guidance, Navigation, and Control Conference and Exhibit. Denver, CO, USA (2000)Google Scholar
  31. 31.
    Shim, H.: Hierarchical flight control system synthesis for rotorcraft-based unmanned aerial vehicles. Ph.D. thesis, Dept. of Mechanical Engineering, University Of California, Berkeley, CA (2000)Google Scholar
  32. 32.
    RAPIDXML Manual: http://rapidxml.sourceforge.net/manual.html (2009). Accessed 18 June 2012
  33. 33.
    ANCL/autopilot—Github: http://github.com/ANCL/autopilot (2012). Accessed 18 June 2012
  34. 34.
    Boost 1.46.1 Library Documentation. http://www.boost.org/doc/libs/1_46_1/ (2012). Accessed 18 June 2012
  35. 35.
    Doxygen: http://doxygen.org (2012). Accessed 18 June 2012
  36. 36.
    QGroundControl: http://qgroundcontrol.org/ (2012). Accessed 18 June 2012
  37. 37.
    Git—Fast Version Control System: http://git-scm.com/. Accessed 18 June 2012
  38. 38.
    Micro Air Vehicle Communication Protocol: http://qgroundcontrol.org/mavlink/start. Accessed 18 June 2012
  39. 39.
    QNX Software Systems Online Infocenter: http://www.qnx.com/developers/docs/6.5.0/index.jsp. Accessed 18 June 2012

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Bryan Godbolt
    • 1
  • Nikolaos I. Vitzilaios
    • 1
    Email author
  • Alan F. Lynch
    • 1
  1. 1.Applied Nonlinear Controls Laboratory, Department of Electrical and Computer EngineeringUniversity of AlbertaEdmontonCanada

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