论文标题
数据驱动的模型减少了两侧力矩匹配
Data-Driven Model Reduction by Two-Sided Moment Matching
论文作者
论文摘要
在这篇简短的论文中，我们提出了一种时间域数据驱动的方法，用于减少模型订单，通过线性系统的两侧力矩匹配。提供了一种从所谓的双面互连的时间域样本中渐近地近似矩阵产物$υπ$的算法。利用此估计的矩阵，我们确定了订单$ν$的唯一缩小订单模型，该模型渐近地与$2ν$不同的插值点相匹配。此外，我们讨论了某些干扰和数据扭曲可能对算法的影响。最后，我们通过基准模型说明了提出的方法的使用。
In this brief paper, we propose a time-domain data-driven method for model order reduction by two-sided moment matching for linear systems. An algorithm that asymptotically approximates the matrix product $ΥΠ$ from time-domain samples of the so-called two-sided interconnection is provided. Exploiting this estimated matrix, we determine the unique reduced-order model of order $ν$, which asymptotically matches the moments at $2 ν$ distinct interpolation points. Furthermore, we discuss the impact that certain disturbances and data distortions may have on the algorithm. Finally, we illustrate the use of the proposed methodology by means of a benchmark model.
