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Communication Dans Un Congrès Année : 2020

Model reduction of linear hybrid systems

Résumé

The paper proposes a model reduction algorithm for linear hybrid systems, i.e., hybrid systems with externally induced discrete events, with linear continuous subsystems, and linear reset maps. The model reduction algorithm is based on balanced truncation. Moreover, the paper also proves an analytical error bound for the difference between the input-output behaviors of the original and the reduced order model. This error bound is formulated in terms of singular values of the Gramians used for model reduction.

Domaines

Automatique
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Dates et versions

hal-02931358 , version 1 (02-09-2021)

Identifiants

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Ion Victor Gosea, Mihaly Petreczky, John Leth, Rafael Wisniewski, Athanasios C. Antoulas. Model reduction of linear hybrid systems. 59th IEEE Conference on Decision and Control (CDC), Dec 2020, Jeju Island (virtual), South Korea. ⟨10.1109/CDC42340.2020.9303918⟩. ⟨hal-02931358⟩
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