Sparsity Enhanced Aerodynamic Parameter Estimation for Nonlinear Aircraft Model

A sparsity-enhanced technique is designed to robustly approximate nonlinear aerodynamic coefficients. The proposed approach addresses the limitations of traditional least squares based methods such as over fitting and ill-conditioning by performing a trade off between complexity of the model and the approximation accuracy. The efficacy of the proposed method is demonstrated through its application to high-fidelity nonlinear simulations of F-16A and X-31aircraft models using data derived from established aerodynamic parameters. A comparative analysis reveals that the proposed approach provides more accurate estimates of unknown coefficients, underscoring its potential to advance aerodynamic modeling and control system design in complex flight regimes.