Model Order Reduction of Second Order Systems Based on Gramians

Abstract

Model order reduction (MOR) is indispensable for managing the complexity of modern systems. In l arge-scale
mechanical systems, it becomes crucial to reduce the order of model while ensuring accuracy and structure preservation for
efficient simulations. This work introduces Frequency Limited Model Order Reduction (FLMOR) techniques, specifically
focusing on gramians. The study showcases the effectiveness of these techniques through the application of FLSOBTpv and
FLSOBTvp algorithms to second-order Linear State-S pace models. Comparative analyses involving Bode plots depict the
precision of the proposed methods in capturing system behavior within s pecified frequency ranges. This research contributes
to the advancement of MOR for intricate engineering systems by leveraging gramians effectively.