Model Reduction for Fractional-Order Port-Hamiltonian Systems in the Loewner Framework
This paper addresses the problem of model order reduction for fractional-order port-Hamiltonian systems (FoPHS) within the Loewner framework. Building on the classical Loewner approach, the study extended the framework to incorporate fractional-order dynamics while preserving the port-Hamiltonian structure in reduced-order models. Specifically, the method was adapted to fractional-order systems by employing right- and left-tangential interpolation data, deriving conditions for constructing an interpolant that retains both the fractional-order behavior and the energy-conserving structure. Additionally, a novel interpolation data selection method was proposed, and numerical simulations validated the reduction approach, demonstrating its effectiveness and accuracy in preserving the system's inherent properties.
Authors
- Jinhua Zhang (ORCID: https://orcid.org/0000-0002-4341-492X)
- Yiheng Wei (ORCID: https://orcid.org/0000-0002-0080-5365)
- Zixi Guan
- Rui Chen (ORCID: https://orcid.org/0000-0002-2628-5847)
Institutions
- Southeast University (CN)
Publication Details
- Published
- 2025-07-04
- DOI
- https://doi.org/10.1109/fasta65681.2025.11138172
- Primary Topic
- Model Reduction and Neural Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00