Model order reduction via time moment modeling and clustering technique

Rahul Singh, V. M. Mishra, J. Singh
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引用次数: 2

Abstract

A high order dynamic system can be reduced by a technology reduces the system through improved pole clustering and pade approximations. In this method the characteristics and property of actual and new reduced systems are remain unchanged. For numerator coefficient pade approximations and for denominator coefficient pole clustering method is used. By comparing the proposed method with existing method it shows that the anticipated method guarantees the immovability of the reduced model and it has some advantages also i.e. calculation straightforwardness, and immovability retention etc. The dominance of the anticipated method is shown through literary examples.
通过时间矩建模和聚类技术降低模型阶数
采用改进的极点聚类和分页近似技术对高阶动态系统进行了降阶。在这种方法中,实际的和新的简化系统的特性和性质保持不变。对于分子系数的页逼近和对于分母系数的极点聚类方法。通过与现有方法的比较,表明所提出的方法不仅保证了简化模型的不动性,而且具有计算简单、不动性保持等优点。预期方法的优势是通过文学实例来证明的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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