State-based approach to the numerical solution of Dirichlet boundary optimal control problems for the Laplace equation

TL;DR

This paper develops a state-based numerical approach for Dirichlet boundary control problems involving the Laplace equation, providing error estimates, optimal mesh-regularization relations, and numerical validation including constrained cases.

Contribution

It introduces a novel state-based framework for Dirichlet boundary control of the Laplace equation with error analysis and optimal parameter relations, including handling of box constraints.

Findings

Derived optimal mesh size and regularization parameter relation.

Established finite element error estimates for the control problem.

Validated theoretical results with numerical examples, including constrained cases.

Abstract

We investigate the Dirichlet boundary control of the Laplace equation, considering the control in $H^{1/2}(\partial \Omega)$, which is the natural space for Dirichlet data when the state belongs to $H^1(\Omega)$. The cost of the control is measured in the $H^{1/2}(\partial \Omega)$ norm that also plays the role of the regularization term. We discuss regularization and finite element error estimates enabling us to derive an optimal relation between the finite element mesh size $h$ and the regularization parameter $\varrho$, balancing the energy cost for the control and the accuracy of the approximation of the desired state. This relationship is also crucial in designing efficient solvers. We also discuss additional box constraints imposed on the control and the state. Our theoretical findings are complemented by numerical examples, including one example with box constraints.