带分数拉普拉卡矩的双线性优化控制问题的自适应有限元逼近

IF 1.4 2区 数学 Q1 MATHEMATICS
Calcolo Pub Date : 2024-09-16 DOI:10.1007/s10092-024-00611-2
Fangyuan Wang, Qiming Wang, Zhaojie Zhou
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引用次数: 0

摘要

我们研究了如何将后验误差估计应用于具有点式控制约束的分数最优控制问题。具体来说,我们要解决的问题是将状态方程表述为分数拉普拉斯方程的积分形式,控制变量作为系数嵌入状态方程中。我们为优化控制问题提出了两种不同的有限元离散化方法。第一种方法采用完全离散方案,其中控制变量使用片断常数函数离散化。第二种方法是半离散方案,不对控制变量进行离散化。利用最优控制问题的一阶最优条件、二阶最优条件和求解正则性分析,我们设计出了后验误差估计。基于已建立的误差估计框架,我们开发了一种自适应细化策略,以帮助达到最佳收敛速率。我们给出了数值实验来说明理论结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Adaptive finite element approximation of bilinear optimal control problem with fractional Laplacian

Adaptive finite element approximation of bilinear optimal control problem with fractional Laplacian

We investigate the application of a posteriori error estimate to a fractional optimal control problem with pointwise control constraints. Specifically, we address a problem in which the state equation is formulated as an integral form of the fractional Laplacian equation, with the control variable embedded within the state equation as a coefficient. We propose two distinct finite element discretization approaches for an optimal control problem. The first approach employs a fully discrete scheme where the control variable is discretized using piecewise constant functions. The second approach, a semi-discrete scheme, does not discretize the control variable. Using the first-order optimality condition, the second-order optimality condition, and a solution regularity analysis for the optimal control problem, we devise a posteriori error estimates. Based on the established error estimates framework, an adaptive refinement strategy is developed to help achieve the optimal convergence rate. Numerical experiments are given to illustrate the theoretical findings.

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来源期刊
Calcolo
Calcolo 数学-数学
CiteScore
2.40
自引率
11.80%
发文量
36
审稿时长
>12 weeks
期刊介绍: Calcolo is a quarterly of the Italian National Research Council, under the direction of the Institute for Informatics and Telematics in Pisa. Calcolo publishes original contributions in English on Numerical Analysis and its Applications, and on the Theory of Computation. The main focus of the journal is on Numerical Linear Algebra, Approximation Theory and its Applications, Numerical Solution of Differential and Integral Equations, Computational Complexity, Algorithmics, Mathematical Aspects of Computer Science, Optimization Theory. Expository papers will also appear from time to time as an introduction to emerging topics in one of the above mentioned fields. There will be a "Report" section, with abstracts of PhD Theses, news and reports from conferences and book reviews. All submissions will be carefully refereed.
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