Parametric identification of nonlinear systems using multiple trials
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It is observed that the harmonic balance (HB) method of parametric identification of nonlinear system may not give right identification results for a single test data. A multiple-trial HB scheme is suggested to obtain improved results in the identification, compared with a single sample test. Several independent tests are conducted by subjecting the system to a range of harmonic excitations. The individual data sets are combined to obtain the matrix for inversion. This leads to the mean square error minimization of the entire set of periodic orbits. It is shown that the combination of independent test data gives correct results even in the case where the individual data sets give wrong results.
KeywordsHarmonic balance Method of least squares Multiple trials Nonlinear system identification
Multidegree of freedom
Discrete Fourier transform
Fast Fourier transform
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