Parameterized model order reduction for linear DAE systems via ε-embedding technique |
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| Institution: | 2. Instituto de Matemática e Estatística, UFG, Campus Samambaia, Goiânia, Goiás 74001-970, Brazil;3. Instituto Federal de Educ. Ciência e Tecnol. de Goiás, IFG, Av. Pedro Ludovico s/n, Loteamento Reny Cury, Anápolis, Goiás 75131-500, Brazil;4. Agencia Nacional de Telecomunicações ANATEL, Distrito Federal, Brasília 70070-940, Brazil;6. Institut fur Prozessdatenverarbeitung und Elektronik, KIT Hermann-von-Helmholtz-Platz 1, Eggenstein-Leopoldshafen, Baden-Württemberg 76344, Germany |
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| Abstract: | In this paper, we present a new method in the reduction of large-scale linear differential-algebraic equation (DAE) systems. The approach is to first change the DAE system into a parametric ordinary differential equation (ODE) system via the ε-embedding technique. Next, based on parametric moment matching, we give the parameterized model order reduction (MOR) method to reduce this parametric system, and a new Arnoldi parameterized method is proposed to construct the column-orthonormal matrix. From the reduced-order parametric system, we get the reduced-order DAE system, which can preserve the structure of the original DAE system. Besides, the parametric moment matching for the reduced-order parametric systems is analyzed. Finally, the effectiveness of our method is successfully illustrated via two numerical examples. |
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