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Adaptive discontinuous Galerkin methods for state constrained optimal control problems governed by convection diffusion equations

机译:对流扩散方程控制的状态约束最优控制问题的自适应不连续Galerkin方法

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摘要

We study a posteriori error estimates for the numerical approximations of state constrained optimal control problems governed by convection diffusion equations, regularized by Moreau-Yosida and Lavrentiev-based techniques. The upwind Symmetric Interior Penalty Galerkin (SIPG) method is used as a discontinuous Galerkin (DG) discretization method. We derive different residual-based error indicators for each regularization technique due to the regularity issues. An adaptive mesh refinement indicated by a posteriori error estimates is applied. Numerical examples are presented to illustrate the effectiveness of the adaptivity for both regularization techniques.
机译:我们研究了对流扩散方程控制的状态约束的最优控制问题的数值逼近的后验误差估计,对流扩散方程由Moreau-Yosida和基于Lavrentiev的技术进行了正则化。上风对称内部罚伽勒金(SIPG)方法用作不连续伽勒金(DG)离散化方法。由于正则性问题,我们为每种正则化技术得出了不同的基于残差的误差指标。应用由后验误差估计指示的自适应网格细化。数值例子说明了两种正则化技术的适应性有效性。

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