Sparse identification of the wing rock dynamics for a blunt-nosed wing body configuration

Uncommanded wing rock motions occurring at high angles of attack, severely limit the flight envelope and maneuverability of modern blunt-nosed wing body configurations. To accurately evaluate and predict these highly nonlinear dynamics, this paper introduces the sparse identification of nonlinear dynamics (SINDy) algorithm to extract analytical rolling models directly from free-to-roll wind tunnel data of a twelve-finned blunt-nosed wing body configuration. The data-driven approach successfully acquires the wing rock dynamics across limit-cycle oscillations, autorotating cases and pitch-up maneuvers. The identified models accurately capture the fundamental characteristics—limit-cycle oscillation amplitudes, dominant frequencies, autorotating rates, and divergent times—with relative errors below 6%. The inclusion of high-order terms identified through SINDy contributes to improved performance compared to prior models, evidenced by reduced mean absolute errors and root-mean-square errors.