Sparsity Enhanced Aerodynamic Parameter Estimation for Nonlinear Aircraft Model

Abstract

This paper introduces an innovative approach to aerodynamic parameter estimation for nonlinear aircraft models, specifically addressing the limitations inherent in traditional methods, such as overfitting and ill-conditioning. Expanding upon the methodology developed in previous research, this study proposes a sparsity-enhanced technique designed to robustly approximate nonlinear aerodynamic coefficients. The efficacy of the proposed method is demonstrated through its application to high-fidelity nonlinear simulations of F-16 and X-31 aircraft 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.