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A Krylov subspace method based on multi-moment matching for model order reduction of large-scale second order bilinear systems

机译:基于多矩匹配的Krylov子空间方法用于大规模二阶双线性系统模型降阶

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In this paper, a Krylov subspace method based on multi-moment matching is utilized for model order reduction of large-scale second order bilinear systems. Accordingly, model order reduction procedure will be directly applied to second order systems which avoids converting them into first order ones. In this way, the main characteristics of the second order system such as symmetry and positive definiteness of the mass and stiffness matrices will be preserved. Furthermore, an electrostatically actuated micro-electro-mechanical system device will be considered as a case study to show the effectiveness of the presented method. Simulation results indicate the excellent performance of the proposed model order reduction method. (C) 2018 Elsevier Inc. All rights reserved.
机译:本文将基于多矩匹配的Krylov子空间方法用于大规模二阶双线性系统的模型降阶。因此,模型阶数减少程序将直接应用于二阶系统,从而避免将它们转换为一阶系统。这样,将保留二阶系统的主要特征,例如质量和刚度矩阵的对称性和正定性。此外,将以静电驱动的微机电系统设备为案例研究,以显示所提出方法的有效性。仿真结果表明,该模型降阶方法具有良好的性能。 (C)2018 Elsevier Inc.保留所有权利。

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