Identifying Parameter-Dependent Volterra Kernels to Predict Aeroelastic Instabilities

Abstract

Flight testing for envelope expansion remains dangerous and costly because of difficulties in accurately predicting the onset of flutter. Approaches have been developed that are able to identify optimal models of the aeroelastic dynamics based on flight data but are not able to predict the responses at all airspeeds. Those previous approaches are extended to include parameter variations in the optimal models. Specifically, parameter-varying models of Volterra kernels are identified for inclusion with theoretical models in aeroelastic analysis. The new approach is applied to a pitch‐plunge system to demonstrate the accuracy achieved in predicting the onset of flutter by analyzing data obtained at lower airspeeds.