Identification of frequency domain model set for linear system based on tailored excitation signals

In this paper, tailored signals are used as excitation signals to obtain a frequency domain model set of a class of plants with uncertainties. After collecting data from identification test, the chirp-z transform is adopted to calculate the discrete frequency spectra of input and output signals. Then the discrete frequency response is obtained. With little priori knowledge of the plant and the type of uncertainties, Laguerre orthogonal basis functions are chosen to construct the nominal frequency domain model. Furthermore, a model set of the plant is determined by using a nonlinear programming algorithm, which can depict model errors and some unknown uncertainties. The result is helpful for system analysis and controller design. The proposed method is illustrated on a two-dimensional wing section model.