Adaptive Regularisation for PDE-Constrained Optimal Control
Abstract
PDE-constrained optimal control problems require regularisation to ensure well-posedness, introducing small perturbations that make the solutions challenging to approximate accurately. We propose a finite element approach that couples both regularisation and discretisation adaptivity, varying both the regularisation parameter and mesh-size locally based on rigorous a posteriori error estimates aiming to dynamically balance induced regularisation and discretisation errors, offering a robust and efficient method for solving these problems. We demonstrate the efficacy of our analysis with several numerical experiments.
Cite
@article{arxiv.2503.11386,
title = {Adaptive Regularisation for PDE-Constrained Optimal Control},
author = {Jenny Power and Tristan Pryer},
journal= {arXiv preprint arXiv:2503.11386},
year = {2025}
}
Comments
29 pages, 14 figures, 5 accompanying videos. Submitted to the special issue of the Journal of Computational and Applied Mathematics, "Boundary and Interior Layers, Computational and Asymptotic Methods - BAIL 2024"