Wavelet-processed flight data for robust aeroservoelastic stability margins

Wavelet analysis for filtering and system identification is used to improve the estimation of aeroservoelastic (ASE) stability margins. Computation of robust stability margins for stability boundary prediction depends on uncertainty descriptions derived from the test data for model validation. Nonideal test conditions, data acquisition errors, and signal processing algorithms cause uncertainty descriptions to be intrinsically conservative. The conservatism of the robust stability margins is reduced with parametric and nonparametric time-frequency analysis of flight data in the model validation process. Nonparametric wavelet processing of data is used to reduce the effects of external disturbances and unmodeled dynamics. Parametric estimates of modal stability are also extracted using the wavelet transform. F-18 High Alpha Research Vehicle ASE flight test data are used to demonstrate improved robust stability prediction by extension of the stability boundary from within the flight envelope to conditions sufficently beyond the actual flight regime. Stability within the flight envelope is confirmed by flight test. Practical aspects and guidelines for efficiency of these procedures are presented for on-line implementation.