Skip to main content

Advertisement

Log in

Minimal Models to Capture the Dynamics of a Rotary Unmanned Aerial Vehicle

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

This paper presents a method for characterising the primary dynamics of a rotary unmanned aerial vehicle. Based on first principles and basic aerodynamics, a mathematical model which explains the rigid body dynamics of a model-scale helicopter is developed. This model is reduced to three simplified decoupled models of attitude dynamics. Empirical test data is collected from a field experiment with significant wind disturbances. The method worked accurately on both uncoupled and fully coupled attitude models. An integral based parameter identification method is presented to identify the unknown intrinsic helicopter parameters as well as model of wind disturbance. An extended Kalman filter system identification method and common nonlinear regression are used for comparison. The EKF was found to be highly dependent on the initial states, so is not suitable for this application which contains significant disturbance and modelling errors. Nonlinear regression proved to be sufficiently accurate but computationally expensive. The proposed integral based parameter identification method was shown to be fast and accurate and is well suited to this application.

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.

Similar content being viewed by others

References

  1. Morris, J.C., van Nieuwstadt, M., Bendotti, P.: Identification and control of a model helicopter in hover. In: American Control Conference, 1994, vol. 1232, pp. 1238–1242, 29 June–1 July 1994

  2. Mettler, B., Kanade, T., Tischler, M.B.: System identification modeling of a model-scale helicopter. In: Vol. Tech. Report CMU-RI-TR-00-03. Robotics Institute, Carnegie Mellon University, Pittsburgh, PA (2000)

  3. Salman, S.A., Puttige, V.R., Anavatti, S.G.: Real-time validation and comparison of fuzzy identification and state-space identification for a UAV platform. In: 2006 IEEE Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, pp. 2138–2143, 4–6 Oct. 2006

  4. Kallapur, A.G., Anavatti, S.G.: UAV linear and nonlinear estimation using extended Kalman filter. In: International Conference on Computational Intelligence for Modelling, Control and Automation, 2006 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, pp. 250–250, 28 Nov.–1 Dec. 2006

  5. Lyashevskiy, S., Yaobin, C.: Nonlinear identification of aircraft. In: Proceedings of the 1996 IEEE International Conference on Control Applications, pp. 327–331, 15–18 Sep. 1996

  6. Kanade, M.L.C.a.a.W.C.M.a.T.: Modeling of small-scale helicopters with integrated first-principles and system-identification techniques. In: Proceedings of the 58th Forum of the American Helicopter Society. Montreal, Canada, pp. 2505–2516 (2002)

  7. Tischler, M.B., Remple, R.K.: Aircraft and rotorcraft system identification: engineering methods with flight-test examples. American Institute of Aeronautics and Astronautics (2006)

  8. Hyunchul Shim, D., Hyoun Jin, K., Sastry, S.: Control system design for rotorcraft-based unmanned aerial vehicles using time-domain system identification. In: Proceedings of the 2000 IEEE International Conference on Control Applications, 2000, pp. 808–813 (2000)

  9. Bruce P.D., S.J.E.F., Kellett M.G.: Maximum likelihood identification of a rotary-wing RPV simulation model from flight-test data. Paper presented at the Atmospheric Flight Mechanics Conference, Boston, MA

  10. Raol, J.R., Girija, G., Singh, J., Engineers, I.o.E.: Modelling and Parameter Estimation of Dynamic Systems. Institution of Electrical Engineers (2004)

  11. Hanbo, Q., Guanqing, C., Hongxing, C., Yiping, Y.: A grey-modeling research on a small-scale autonomous helicopter. In: International Conference on Information Engineering and Computer Science, 2009. ICIECS 2009, pp. 1–4, 19–20 Dec. 2009

  12. Hann, C.E., M.S., Rao, A., Winn, O., Wongvanich, N., Chen, X.: Minimal modelling approach to describe turbulent rocket roll dynamics in a vertical wind tunnel. J. Aerosp. Eng. 226(9), 1042–1060 (2012)

    Google Scholar 

  13. Hann, C.E., Chase, J.G., Lin, J., Lotz, T., Doran, C.V., Shaw, G.M: Integral-based parameter identification for long-term dynamic verification of a glucose-insulin system model. Comput. Methods Programs Biomed. 77(3), 259–270 (2005)

    Article  Google Scholar 

  14. Hann, C.E., Chase, J.G., Ypma, M.F., Elfring, J., Nor, N.M.H., Lawrence, P., Shaw, G.M.: The impact of parameter identification methods on drug therapy control in an intensive care unit. Open Med. Inform. J. 2, 92–104 (2008)

    Article  Google Scholar 

  15. Padfield, G.D.: Helicopter Flight Dynamics: The Theory and Application of Flying Qualities and Simulation Modelling. Blackwell Publishing (2007)

  16. Raptis, I.A., Valavanis, K.P., Moreno, W.A.: System identification and discrete nonlinear control of miniature helicopters using backstepping. J. Intell. Robot. Syst. 55(2–3), 223–243 (2009). doi:10.1007/s10846-008-9295-5

    Article  MATH  Google Scholar 

  17. Castillo, P., Lozano, R., Dzul, A.E.: Modelling and Control of Mini-flying Machines. Springer, New York (2005)

  18. Kim, S.K., Tilbury, D.M.: Mathematical modeling and experimental identification of an unmanned helicopter robot with flybar dynamics. J. Robot. Syst. 21(3), 95–116 (2004). doi:10.1002/rob.20002

    Article  Google Scholar 

  19. Docherty, P.D., Chase, J.G., Lotz, T.F., Hann, C.E., Shaw, G.M., Berkeley, J.E., TeMorenga, L., Mann, J.I., McAuley, K.: Independent cohort cross-validation of the real-time DISTq estimation of insulin sensitivity. Comput. Methods Prog. Biomed. 102(2), 94–104 (2011). doi:10.1016/j.cmpb.2010.08.002

    Article  Google Scholar 

  20. Wong, X.W., Chase, J.G., Shaw, G.M., Hann, C.E., Lotz, T., Lin, J., Singh-Levett, I., Hollingsworth, L.J., Wong, O.S.W., Andreassen, S.: Model predictive glycaemic regulation in critical illness using insulin and nutrition input: a pilot study. Med. Eng. Phys. 28(7), 665–681 (2006). doi:10.1016/j.medengphy.2005.10.015

    Article  Google Scholar 

  21. Martini, A., Léonard, F., Abba, G.: Dynamic modelling and stability analysis of model-scale helicopters under wind gust. J. Intell. Robot. Syst. 54(4), 647–686 (2009). doi:10.1007/s10846-008-9280-z

    Article  Google Scholar 

  22. Chowdhary, G.a.L., Sven: Control of a VTOL UAV via online parameter estimation. Paper presented at the AIAA Guidance, Navigation, and Control Conference and Exhibit, San Francisco, California, USA

  23. Abhijit, G. Kallapur, S.S.A.a.S.G.A.: Application of extended Kalman Filter towards UAV identification. In: Autonomous Robots and Agents, pp. 199–207. Springer, Berlin/Heidelberg (2007)

    Google Scholar 

  24. Ozbek, L.v.E., M: Online estimation of the state and the parameters in compartmental models using extended Kalman filter. In: Trofimova, W.H.S.a.I. (ed.) Nonlinear Dynamics in the Life and Social Sciences, pp. 262–271. IOS Press (2001)

  25. Gavrilets, V., E.F., Mettler, B., Piedmonte, M., Feron, E.: Aggressive maneuvering of small autonomous helicopters: a human-centered approach. Int. J. Robot. Res. 20, 795–807 (2001)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rejina Ling Wei Choi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Choi, R.L.W., Hann, C.E. & Chen, X. Minimal Models to Capture the Dynamics of a Rotary Unmanned Aerial Vehicle. J Intell Robot Syst 75, 569–593 (2014). https://doi.org/10.1007/s10846-013-9993-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-013-9993-5

Keywords

Navigation