Panel flutter model identification using the minimum model error method on the forced response measurements

This work illustrates application of the minimum model error system identification method to obtain the nonlinear state space models of a fluttering panel. Identification using position and velocity data from forced response of the panel is presented here. The response was numerically simulated using two different discretization approaches: through finite differences and using the Galerkin's method. Data from two different parts of response time history were considered. First, data where transients due to initial conditions and the forcing were present were used for identification. Then, data when only transients due to forcing were present were used for identification. The models obtained using the forced response of the panel were able to capture the behavior of the true system relatively accurately. Identification of models of different sizes is also discussed. Reduced size models can be successfully created from the forced response data using the minimum model, error method. It is demonstrated that the number of degrees of freedom in the model attempted to be identified should be consistent with the number modes observed in the measurements. The response surface method was successfully applied to generate models for various flow regimes.