A WAVELET-BASED APPROACH FOR THE IDENTIFICATION OF LINEAR TIME-VARYING DYNAMICAL SYSTEMS

A novel procedure is developed for the identification of linear discrete models of dynamical systems from noisy data. Of particular interest is the application of the methodology to time-varying systems. The procedure is based on a representation of the governing differential equations with respect to a wavelet basis, and the formulation of an inverse algebraic problem in the associated subspace. The effect of noisy data is considered and numerical simulations demonstrating the applicability of the method to single- and multi-degree-of-freedom dynamical systems are presented.