State-space identification of nonlinear flight dynamics

A new identification concept is offered in this paper, and it is shown how to identify the unknown parameters of nonlinear flight dynamic systems assuming that a generic nonlinear model is known. To ensure robustness and parameter convergence, nonlinear error mappings are used, and the Lyapunov second method is employed to approach the analysis of convergence. The explored method is applied to a longitudinal aerodynamic model of a high-angle-of-attack (high-alpha) fighter aircraft. In particular, the parameters of an unsteady flight model are identified.