Robust second-order VSBDF2 finite element schemes for parabolic distributed optimal control problems

IF 2.1 2区 数学 Q1 MATHEMATICS, APPLIED
Caijie Yang, Tongjun Sun
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引用次数: 0

Abstract

In this paper, we further investigate the variable-step BDF2 (VSBDF2) finite element schemes for solving control constrained distributed optimal control problems governed by parabolic equations, where the state, co-state and control variables are approximated by piecewise linear functions. We first propose the VSBDF2 backward and forward formulas, respectively. Then, motivated by the discrete orthogonal convolution (DOC) and discrete complementary convolution (DCC) backward kernels (Liao and Zhang, 2021; Zhang and Zhao, 2022), we introduce the novel DOC and DCC forward kernels. Utilizing the new analytical tool of backward and forward kernels concerning the DOC and DCC, we can obtain a priori error estimates with the optimal second-order temporal accuracy for the parabolic distributed optimal control problem under the restriction condition 1/4.8645rk4.8645. Moreover, our analysis also shows that the initial solutions y1 and pN1 obtained by VSBDF1 backward and forward formulas (i.e., the variable-step backward and forward Euler formulas) do not result in the loss of accuracy with 1/4.8645rk4.8645. Numerical experiments are provided to validate our theoretical analysis.
抛物型分布最优控制问题的鲁棒二阶VSBDF2有限元格式
在本文中,我们进一步研究了用分段线性函数逼近状态、协状态和控制变量的变步长BDF2 (VSBDF2)有限元格式求解控制约束分布最优控制问题。我们首先分别提出了VSBDF2的后向和正向公式。然后,在离散正交卷积(DOC)和离散互补卷积(DCC)后向核的激励下(Liao and Zhang, 2021;Zhang and Zhao, 2022),我们介绍了新的DOC和DCC前向核。对于约束条件为1/4.8645≤rk≤4.8645的抛物型分布最优控制问题,利用新的关于DOC和DCC的后向核和正向核的分析工具,我们可以得到具有最优二阶时间精度的先验误差估计。此外,我们的分析还表明,通过VSBDF1后向和正向公式(即变步长后向和正向欧拉公式)得到的初始解y1和pN−1不会导致精度在1/4.8645≤rk≤4.8645范围内的损失。数值实验验证了理论分析的正确性。
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来源期刊
CiteScore
5.40
自引率
4.20%
发文量
437
审稿时长
3.0 months
期刊介绍: The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.
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