Reduced order flutter modeling based on the Hammerstein model with μ-Markov structure and correlation identification method

This paper presents an approach for reduced order flutter modeling based on the Hammerstein model and system identification. The Hammerstein model considered is prescribed a μ-Markov structure in the linear block, and its identification employs a correlation-based method for separable input processes. This combination of model and identification method has been shown in a previous work to accurately identify the linear block, which is vital to bifurcation analysis. Using computational fluid dynamics data and an experimental benchmark, it is shown that the proposed approach yields better accuracy relative to the benchmark as well as by model validation.

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