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This paper explores the difficulties of aircraft system identification, specifically parameter estimation, for a rudderless aircraft. A white box method is used in conjunction with a nonlinear six degree-of-freedom aerodynamic model for the equations of motion in order to estimate 33 parameters that govern the aerodynamic, inertial, and propulsion forces within the mathematical model. The analysis is conducted in the time-domain of system identification. Additionally, all the parameters are estimated using a single flight rather than a series of shorter flights dedicated to estimating specific sets of parameters as is typically done. A final flight plan is developed with a mixture of lateral maneuvers interspersed throughout the flight to accentuate the significance of the lateral parameters during estimation. Certain parameters were ill-conditioned for parameter estimation using the mathematical model and final flight plan derived in this paper. The gradient-based optimization technique used in the estimation algorithm struggled to accurately estimate all 33 in a single flight due to the abundance of local minima within the solution space. The results of this work may provide a few insights for parameter estimation. First, to understand why system identification is performed the way it is currently done through multiple different flight maneuvers. Second, to gain some visual insight to the behavior of the nonlinear six degree-of-freedom aerodynamic model that describes the motion of fixed wing aircraft. This work may also be helpful in determining which parameters might likely be estimated together and which may struggle due to coupled dynamic relations within the mathematical model.
Thurgood, J. W., and Hunsaker, D. F., "Sensitivity and Estimation of Flying-Wing Aerodynamic, Propulsion, and Inertial Parameters Using Simulation," AIAA SciTech Forum Virtual Event, January 2021, AIAA-2021-1528, DOI: 10.2514/6.2021-1528