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arXiv 1810.02415math.NAcs.NAmath.OC
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针对斯托克斯方程点跟踪最优控制问题的自适应有限元方法

Adaptive finite element methods for the pointwise tracking optimal control problem of the Stokes equations

Universidad Técnica Federico Santa María(智利弗雷德里科·圣玛丽亚技术大学)

Alejandro Allendes, Francisco Fuica, Enrique Otárola, Daniel Quero

AI总结:

本文提出并分析了针对斯托克斯方程点跟踪最优控制问题的可靠且高效的后验误差估计器,该问题涉及最小化包含速度场点评估的代价函数,导致伴随问题具有减少的正则性性质,并考虑了控制变量的约束。

摘要:

我们提出并分析了针对斯托克斯方程点跟踪最优控制问题的可靠且高效的后验误差估计器。该线性二次最优控制问题涉及最小化一个包含解状态方程的速度场点评估的代价函数。这导致伴随问题具有线性组合的狄拉克测度作为激励项,其解表现出减少的正则性性质。我们还考虑了控制变量的约束。所提出的后验误差估计器可以分解为四个贡献之和:三个与状态和伴随方程的离散化相关,另一个与控制变量的离散化相关。基于所设计的后验误差估计器,我们设计了一个简单的自适应策略,展示了我们的理论并表现出有竞争力的性能。

英文摘要:

We propose and analyze a reliable and efficient a posteriori error estimator for the pointwise tracking optimal control problem of the Stokes equations. This linear-quadratic optimal control problem entails the minimization of a cost functional that involves point evaluations of the velocity field that solves the state equations. This leads to an adjoint problem with a linear combination of Dirac measures as a forcing term and whose solution exhibits reduced regularity properties. We also consider constraints on the control variable. The proposed a posteriori error estimator can be decomposed as the sum of four contributions: three contributions related to the discretization of the state and adjoint equations, and another contribution that accounts for the discretization of the control variable. On the basis of the devised a posteriori error estimator, we design a simple adaptive strategy that illustrates our theory and exhibits a competitive performance.

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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