Identification of nonlinear systems driven by random multisine signals

Abstract

In this paper, we propose a novel method for identification of cubically nonlinear systems using random multisine signals. The proposed method is based on analysis of higher-order auto-moment spectra of random multisine signals. We show that, using properly designed random multisines as driving signals, nonlinear systems can be identified with a highly computationally efficient algorithm with ease. The correctness of the analysis and the effectiveness of the derived algorithm are verified by domputer simulation.