Proceedings of the 2017 International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2017)

Superconvergence of Variational Discretization for Bilinear Elliptic Optimization Problems

Authors
Yuelong Tang, Yuchun Hua
Corresponding Author
Yuelong Tang
Available Online May 2017.
DOI
10.2991/ammsa-17.2017.65How to use a DOI?
Keywords
convergence; superconvergence; variational discretization; bilinear elliptic optimal control problems
Abstract

In this paper, variational discretization approximation of bilinear elliptic optimal control problems is considered. Firstly, we construct a variational discretization method for the bilinear elliptic optimal control problem with control constraints. Secondly, we derive the convergence of the approximation scheme. Thirdly, we analyze the superconvergence. Finally, we present a numerical example to conform our theoretical results.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2017)
Series
Advances in Intelligent Systems Research
Publication Date
May 2017
ISBN
10.2991/ammsa-17.2017.65
ISSN
1951-6851
DOI
10.2991/ammsa-17.2017.65How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yuelong Tang
AU  - Yuchun Hua
PY  - 2017/05
DA  - 2017/05
TI  - Superconvergence of Variational Discretization for Bilinear Elliptic Optimization Problems
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2017)
PB  - Atlantis Press
SP  - 290
EP  - 293
SN  - 1951-6851
UR  - https://doi.org/10.2991/ammsa-17.2017.65
DO  - 10.2991/ammsa-17.2017.65
ID  - Tang2017/05
ER  -