A Frequency-Domain Validation Test for Uncertainty Models Having White Noise and Unmodeled Dynamics

Abstract

In this paper, we propose a new frequency-domain validation test for uncertainty models having white noises and norm-bounded unmodeled dynamics. In this method, a statistical whiteness test is integrated into the deterministic model validation methodology and we consider the whiteness test based on the averaged periodogram of data segments in order to reduce the validation problem into a convex problem with less computation burden. One of the distinguished features of our method is that the quality of the validation test can be improved by increasing the data segments because of the whiteness test. Also, one of the merits of our frequency-domain validation test is that we need a priori information in time-domain only. A numerical example is given to illustrate the effectiveness of the proposed method.