Data-Driven Parametric Modeling of Linear Systems in Frequency Domain

Abstract

This paper shows how to model linear plants using data obtained by simple experiments, such as those performed in data-driven controls. The method estimates the frequency response of the plant and uses it to estimate its transfer function with the prediction error method in the frequency domain. The frequency domain prediction error method allows the selection of the frequency components to be used for modeling easily and suppresses the effects of noise on the modeling results. Numerical experiments of open-loop modeling and actual experiments of closed-loop modeling with velocity control system for a two-inertia system demonstrate the effectiveness of the proposed method.