Abstract

Model uncertainty directly affects the accuracy of robust flutter and limit-cycle-oscillation (LCO) analysis. Using a data-based method, the bounds of an uncertain block-oriented aeroelastic system with nonlinearity are obtained in the time domain. Then robust LCO analysis of the identified model set is performed. First, the proper orthonormal basis is constructed based on the on-line dynamic poles of the aeroelastic system. Accordingly, the identification problem of uncertain model is converted to a nonlinear optimization of the upper and lower bounds for uncertain parameters estimation. By replacing the identified memoryless nonlinear operators by its related sinusoidal-input describing function, the Linear Fractional Transformation (LFT) technique is applied to the modeling process. Finally, the structured singular value (µ) method is applied to robust LCO analysis. An example of a two-degree wing section is carried out to validate the framework above. Results indicate that the dynamic characteristics and model uncertainties of the aeroelastic system can be depicted by the identified uncertain model set. The robust LCO magnitude of pitch angle for the identified uncertain model is lower than that of the nominal model at the same velocity. This method can be applied to robust flutter and LCO prediction.

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