文章基本信息

标题：Reinforcement Learning-based Model Reduction for Partial Differential Equations
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作者：Mouhacine Benosman ; Ankush Chakrabarty ; Jeff Borggaard 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：7704-7709
DOI：10.1016/j.ifacol.2020.12.1515
语种：English
出版社：Elsevier
摘要：AbstractThis paper is dedicated to the problem of stable model reduction for partial differential equations (PDEs). We propose to use proper orthogonal decomposition (POD) method to project the PDE model into a lower dimensional given by an ordinary differential equation (ODE) model. We then stabilize this model, following the closure model approach, by proposing to use reinforcement learning (RL) to learn an optimal closure model term. We analyze the stability of the proposed RL closure model and show its performance on the coupled Burgers equation.