论文标题
通过低级近似值的气管管道网络的有效状态估计
Efficient State Estimation for Gas Pipeline Networks via Low-Rank Approximations
论文作者
论文摘要
在本文中，我们研究了基于投影的低级别近似值在卡尔曼过滤中的性能。对于大规模的气管网络网络而言，结构提供模型订单的降低已成为一种有利的方法，可以减少计算工作的方式来计算准确的解决方案。根据州的估计，我们建议将这些低级模型与卡尔曼过滤结合起来，并在估计的效率和质量方面显示了该程序对确定的低级别卡尔曼过滤器的优势。
In this paper we investigate the performance of projection-based low-rank approximations in Kalman filtering. For large-scale gas pipeline networks structure-preserving model order reduction has turned out to be an advantageous way to compute accurate solutions with much less computational effort. For state estimation we propose to combine these low-rank models with Kalman filtering and show the advantages of this procedure to established low-rank Kalman filters in terms of efficiency and quality of the estimate.
