Structure-preserving model reduction for marginally stable LTI systems
Liqian Peng, Kevin Carlberg

TL;DR
This paper introduces a novel structure-preserving model reduction technique for marginally stable LTI systems, ensuring the reduced model maintains marginal stability and accurately captures system energy characteristics.
Contribution
The work develops a new reduction method that preserves marginal stability by decomposing systems and applying specialized projection techniques, unlike traditional Lyapunov-based approaches.
Findings
Successfully reduces system dimension while maintaining stability.
Preserves pure marginal stability and energy properties.
Numerical examples demonstrate accuracy and stability retention.
Abstract
This work proposes a structure-preserving model reduction method for marginally stable linear time-invariant (LTI) systems. In contrast to Lyapunov-stability-based approaches---which ensure the poles of the reduced system remain in the open left-half plane---the proposed method preserves marginal stability by reducing the subsystem with poles on the imaginary axis in a manner that ensures those poles remain purely imaginary. In particular, the proposed method decomposes a marginally stable LTI system into (1) an asymptotically stable subsystem with eigenvalues in the open left-half plane and (2) a pure marginally stable subsystem with a purely imaginary spectrum. We propose a method based on inner-product projection and the Lyapunov inequality to reduce the first subsystem while preserving asymptotic stability. In addition, we demonstrate that the pure marginally stable subsystem is a…
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Taxonomy
TopicsModel Reduction and Neural Networks · Numerical methods for differential equations · Advanced Numerical Methods in Computational Mathematics
