A Robust Frequency-Domain-Based Order Reduction Scheme for Linear Time-Invariant Systems

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Mahata, Shibendu
Herencsár, Norbert
Alagoz, Baris Baykant
Yeroglu, Celaleddin

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Mark

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IEEE
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This paper presents a robust model order reduction technique with guaranteed stability, minimum phase, and matched steady-state response for linear time-invariant single-input-single-output systems. The proposed approach is generalized, allowing the designer to select any desired order of the reduced-order model (ROM). In contrast to the published literature, which primarily uses the time-domain behavior, the proposed technique utilizes the frequency-domain information of the full-order system. The suggested strategy allows the determination of the optimal ROM in a single step, simpler than the various recently reported mixed methods. The robustness is demonstrated using convergence studies and statistical measures about the final solution quality and model coefficients. The superiority over the recent literature is illustrated through four numerical examples using various time-domain and frequency response performance metrics.
This paper presents a robust model order reduction technique with guaranteed stability, minimum phase, and matched steady-state response for linear time-invariant single-input-single-output systems. The proposed approach is generalized, allowing the designer to select any desired order of the reduced-order model (ROM). In contrast to the published literature, which primarily uses the time-domain behavior, the proposed technique utilizes the frequency-domain information of the full-order system. The suggested strategy allows the determination of the optimal ROM in a single step, simpler than the various recently reported mixed methods. The robustness is demonstrated using convergence studies and statistical measures about the final solution quality and model coefficients. The superiority over the recent literature is illustrated through four numerical examples using various time-domain and frequency response performance metrics.

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IEEE Access. 2021, vol. 9, issue 1, p. 165773-165785.
https://ieeexplore.ieee.org/document/9648306

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Peer-reviewed

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en

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Except where otherwised noted, this item's license is described as Creative Commons Attribution 4.0 International
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