Attitude Dynamics Identification of Unmanned Aircraft Vehicle

  • Salman Shaaban Ali (School of Aerospace, Civil and Mechanical Engineering, Australian Defence Force Academy) ;
  • Sreenatha Anavatti G. (School of Aerospace, Civil and Mechanical Engineering, Australian Defence Force Academy) ;
  • Choi, Jin-Young (School of Electrical Engineering, Seoul National University)
  • Published : 2006.12.30

Abstract

The role of Unmanned Aircraft Vehicles(UAVs) has been increasing significantly in both military and civilian operations. Many complex systems, such as UAVs, are difficult to model accurately because they exhibit nonlinearity and show variations with time. Therefore, the control system must address the issues of uncertainty, nonlinearity, and complexity. Hence, identification of the mathematical model is an important process in controller design. In this paper, attitude dynamics identification of UAV is investigated. Using the flight data, nonlinear state space model for attitude dynamics of UAV is derived and verified. Real time simulation results show that the model dynamics match experimental data.

Keywords

References

  1. E. A. Morelli, 'System identification programs for aircraft (SIDPAC),' Proc. of AIAA Atmospheric Flight Mechanics Conference, Monterey, Aug. 5-8 2002
  2. S. E. Lyshevski, 'State-space identification of nonlinear flight dynamics,' Proc. of the IEEE International Conference on Control Applications, Hartford, CT, pp. 496-498, October 5-7, 1997
  3. S. E. Lyshevski and Y. Chen, 'Nonlinear identification of aircraft,' Proc. of IEEE International Conference on Control Applications, Dearborn, MI, pp. 327-331, September 1518, 1996
  4. S. E. Lyshevski, 'Identification of nonlinear flight dynamics: Theory and practice,' IEEE Trans. on Aerospace and Electronic Systems, vol. 36, no. 2, pp. 383-392, April, 2000 https://doi.org/10.1109/7.845215
  5. S. E. Lyshevski, 'Identification of nonlinear systems with noisy data: A nonlinear mappingbased concept in time domain,' Proc. of American Control Conference, vol. 2, pp. 1634-1635, June 25-27, 2001
  6. V. Pappano, S. E. Lyshevski, and B. Friedland, 'Nonlinear identification of induction motor parameters,' Proc. of the American Control Conference, vol. 5, pp. 3569-3573, June 1999
  7. J. Roskam, Airplane Flight Dynamics and Automatic Flight Controls, DAR corporation, Lawrence, Kan, 1995