DOI QR코드

DOI QR Code

Quasi Steady Stall Modelling of Aircraft Using Least-Square Method

  • Verma, Hari Om (Department of Aerospace Engineering, IIT Kharagpur) ;
  • Peyada, N.K. (Department of Aerospace Engineering, IIT Kharagpur)
  • Received : 2018.10.13
  • Accepted : 2019.12.28
  • Published : 2020.06.30

Abstract

Quasi steady stall is a phenomenon to characterize the aerodynamic behavior of aircraft at high angle of attack region. Generally, it is exercised from a steady state level flight to stall and its recovery to the initial flight in a calm weather. For a theoretical study, such maneuver is demonstrated in the form of aerodynamic model which consists of aircraft's stability and control derivatives. The current research paper is focused on the appropriate selection of aerodynamic model for the maneuver and estimation of the unknown model coefficients using least-square method. The statistical accuracy of the estimated parameters is presented in terms of standard deviations. Finally, the validation has been presented by comparing the measured data to the simulated data from different models.

Keywords

References

  1. B. Etkin, Dynamics of Atmospheric Flight, Wiley, New York, 1972.
  2. R. V. Jategaonkar, Flight Vehicle System Identification: A Time Domain Methodology, Vol. 216, Progress in Astronautics and Aeronautics, 1st ed., AIAA, Reston, VA, 2006.
  3. P. G. Hamel, and R. V. Jategaonkar, "Evolution of flight vehicle system identification," Journal of Aircraft, vol. 33, no. 1, pp. 9-28, 1996. https://doi.org/10.2514/3.46898
  4. M. G. Goman and A. N. Khrabrov, "State-space representation of aerodynamic characteristics of an aircraft at high angles of attack," Journal of Aircraft, vol. 31, no. 5, pp. 1109-1115, 1994. https://doi.org/10.2514/3.46618
  5. D. Fischenberg, "Identification of an unsteady aerodynamic stall model from flight test data," Proc. AIAA Atmospheric Flight Mechanics Conf., Baltimore, pp. 138-146, 1995.
  6. D. Fischenberg and R.V. Jategaonkar, "Identification of aircraft stall behavior from flight test data," In RTO SCI Symposium on System Identification for Integrated Aircraft Development and Flight Testing, 1998.
  7. N. K. Peyada, A. K. Ghosh, "Aircraft parameter estimation using new filtering technique based on neural network and Gauss-Newton method", Aeronautical Journal, vol. 113, no. 1142, pp. 243-252, 2009. https://doi.org/10.1017/S0001924000002918
  8. R. Kumar and A. K. Ghosh, "Nonlinear longitudinal aerodynamic modeling using neural Gauss-Newton method," Journal of Aircraft, vol. 48, no. 5, pp.1809-1812, 2011. https://doi.org/10.2514/1.C031253
  9. S. Saderla, R. Dhayalan and A. K. Ghosh, "Parameter estimation from near stall flight data using conventional and neural-based methods", Defense Science Journal, vol. 67, no 1, pp. 03-11, Dec. 2016. https://doi.org/10.14429/dsj.67.9995
  10. H. O. Verma and N. K. Peyada, "Parameter estimation of stable and unstable aircraft using extreme learning machine", AIAA Atmospheric Flight Mechanics Conf. 2018, AIAA 2018-0526, Florida, USA.
  11. E. A. Morelli, "Practical aspects of the equation error method for aircraft parameter estimation," AIAA-2006-6144, AIAA Atmospheric Flight Mechanics Conf., Keystone, CO, August 2006.
  12. R. V. Jategaonkar and E. Plaetschke, "Algorithms for aircraft parameter estimation accounting for process and measurement noise," Journal of Aircraft, vol. 26, no. 4, pp. 360-372, 1989 https://doi.org/10.2514/3.45769
  13. R. V. Jategaonkar and F. Thielecke, "Evaluation of parameter estimation methods for unstable aircraft," Journal of Aircraft, vol. 31, no. 3, pp. 51-519, 1994.
  14. E. A. Morelli, "Efficient global aerodynamic modeling from flight data," 50th Aerospace Sciences Meeting, Nashville, Tennessee, AIAA-2012-1050, Jan. 2012.
  15. D. I. Ignatyev and A. N. Khrabrov, "Neural network modeling of unsteady aerodynamic characteristics at high angles of attack," Aerospace Science and Technology, vol. 41, pp. 106-115, 2015. https://doi.org/10.1016/j.ast.2014.12.017
  16. Q. Wang, W. Q. Qian and K. F. He, "Unsteady aerodynamic modeling at high angles of attack using support vector machines," China Journal of Aeronautics, vol. 28, no. 3, pp. 659-68, 2015. https://doi.org/10.1016/j.cja.2015.03.010