Multivariable frequency-response curve fitting with application to modal parameter estimation

This paper presents a computational approach for the frequency-domain identification of multivariable, discrete-time transfer function models based on a cost function minimization. The algorithm is optimized for the parametric characterization of complex high-order multivariable systems requiring a large number of model parameters, including sparse matrix methods and QR-projections for the reduction of computation time and memory requirements. The algorithm supports a multivariable frequency-dependent weighting, which generally improves the quality of the transfer function model estimate. The overall approach is successfully demonstrated for a typical case encountered in experimental structural dynamics modelling (using modal analysis) and compared with related algorithms in order to assess the gain in computational efficiency.