Work

Moment matching-based model reduction for systems with linear quadratic output

Year: 2025

Type: conference-paper

Abstract: In this paper, we present a time-domain moment matching approach for the model reduction of linear quadratic output (LQO) systems. The moment of an LQO system, is the output function of a projected state, based on the unique solution of a Sylvester equation. We determine a family of reduced-order parameterized models matching the given moment. First, we seek low-order approximations that preserve selected poles of a given LQO system. Secondly, we propose a gradient method to compute the parameters yielding the reduced order model that minimizes the ℋ2error norm. Then, we address a mixed ℋ2error norm-(partially) prescribed poles problem to obtain the approximation minimizing the ℋ2error norm, in the class of reduced order models with prescribed poles. To solve the mixed problem, we propose a projected gradient method. Finally, the theory is illustrated on an LQO system of order thirty.

Source: Proceedings of the IEEE Conference on Decision & Control, including the Symposium on Adaptive Processes

DOI: 10.1109/cdc57313.2025.11312362

Authors: T. C. Ionescu, O. V. Iftime, I. Necoara

Institutions: Universitatea Națională de Știință și Tehnologie Politehnica București, University of Groningen

Language: English

Topic: Advanced Control Systems Design

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7123356353

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