Identification of nonlinear flight dynamics: theory and practice

This article presents an innovative time-domain nonlinear mapping-based identification method. The method reported is applied to identify the unknown parameters of multivariable dynamic systems which are mapped by nonlinear differential equations. A systematic identification method is introduced, and a novel algorithm is developed using nonlinear error maps. An analysis of parameter convergence is provided and the regions of convergence can be found using the second method of Lyapunov. Innovative nonquadratic Lyapunov functions are designed and used. Analytical and numerical studies are performed to illustrate and validate the identification concept. The unsteady flight of a high-alpha aircraft in the longitudinal axis is chosen as a nonlinear case study. The unknown parameters are identified. Simulation results show that the model dynamics match the experimental data. The reported example demonstrates that the time-domain nonlinear mapping-based identification method ensures robustness and reduces major shortcomings in stability, convergence, and computational efficiency compared with other algorithms available.