Improved frequency response function estimation by Gaussian process regression with prior knowledge⁎This research was supported in part by the Fund for Scientific Research (FWO Vlaanderen), and in part by the Flemish Government (Methusalem Grant METH1). Issue 7 (2021) - Hallemans, N.; Pintelon, R.; Peumans, D.; Lataire, J.
Abstract: Kernel-based modelling of dynamical systems offers important advantages such as imposing stability, causality and smoothness on the estimate of the model. Here, we improve the existing frequency domain kernel-based approach for estimating the transfer function of a linear time-invariant system from noisy data. This is done by introducing prior knowledge in the kernel. We use a local rational modelling technique to determine the most significant poles, and include these poles as prior knowledge in the kernel. This results in accurate models for the identification of lightly-damped systems.