Frequency-Domain Analysis for Nonlinear Systems With Time-Domain Model Parameter Uncertainty

Frequency-domain analysis of dynamic systems is important across many areas of engineering. However, while there are many analysis methods for linear systems, the problem is much less widely studied for nonlinear systems. Frequency-domain analysis of nonlinear systems using frequency response functions (FRFs) is particularly important to reveal resonances, super/subh-armonics, and energy transfer across frequencies. In this paper, the novel contribution is a time-domain, model-based approach to describing the uncertainty of nonlinear systems in the frequency domain. The method takes a nonlinear input-output time-domain model that has normally distributed parameters and propagates that uncertainty into the frequency domain using analytic expressions based on FRFs. We demonstrate the approach on both synthetic examples of nonlinear systems and a real-world nonlinear system identified from experimental data. We benchmark the proposed approach against a brute-force technique based on Monte Carlo sampling and show that there is good agreement between the methods.