arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2007.15988math.OCmath.DS
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基于低秩近似的燃气管网状态估计

Efficient State Estimation for Gas Pipeline Networks via Low-Rank Approximations

Nadine Stahl, Nicole Marheineke

摘要:

在本文中,我们研究的性能,基于投影的低秩近似卡尔曼滤波。对于大规模的天然气管网,结构保持模型降阶已被证明是一种有利的方法,以更少的计算工作量计算精确的解决方案。对于状态估计,我们建议将这些低秩模型与卡尔曼滤波相结合,并在估计的效率和质量方面展示了这种方法对建立低秩卡尔曼滤波器的优势。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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