Offline accuracy is not enough: closed-loop instability and stabilisation of a wall-sensor neural estimator in opposition control
This paper demonstrates that while a neural estimator trained on wall-shear-stress data can accurately reconstruct near-wall flow quantities offline, it fails in closed-loop opposition control due to distribution shifts caused by the controller itself, necessitating spectral consistency constraints and closed-loop retraining to achieve stable, drag-reducing performance.