Interpolatory model reduction of parameterized bilinear dynamical systems

被引:0
|
作者
Andrea Carracedo Rodriguez
Serkan Gugercin
Jeff Borggaard
机构
[1] Virginia Tech,Department of Mathematics
来源
Advances in Computational Mathematics | 2018年 / 44卷
关键词
Model reduction; Parametric; Bilinear; Interpolation; 41A05; 93A15; 93C10; 35B30; 93C15; 93B40;
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学科分类号
摘要
Interpolatory projection methods for model reduction of nonparametric linear dynamical systems have been successfully extended to nonparametric bilinear dynamical systems. However, this has not yet occurred for parametric bilinear systems. In this work, we aim to close this gap by providing a natural extension of interpolatory projections to model reduction of parametric bilinear dynamical systems. We introduce necessary conditions that the projection subspaces must satisfy to obtain parametric tangential interpolation of each subsystem transfer function. These conditions also guarantee that the parameter sensitivities (Jacobian) of each subsystem transfer function are matched tangentially by those of the corresponding reduced-order model transfer function. Similarly, we obtain conditions for interpolating the parameter Hessian of the transfer function by including additional vectors in the projection subspaces. As in the parametric linear case, the basis construction for two-sided projections does not require computing the Jacobian or the Hessian.
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页码:1887 / 1916
页数:29
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