Maximum-norm a posteriori error estimates for an optimal control problem
Alejandro Allendes, Enrique Otarola, Richard Rankin, Abner J. Salgado
TL;DR
This paper develops a reliable max-norm a posteriori error estimator for control-constrained linear-quadratic optimal control problems, achieving optimal convergence rates in adaptive algorithms.
Contribution
It introduces a novel max-norm a posteriori error estimator that is both reliable and efficient for this class of optimal control problems.
Findings
Estimator achieves optimal convergence rates
Ensures reliability and efficiency in adaptive methods
Applicable to control-constrained linear-quadratic problems
Abstract
We analyze a reliable and efficient max-norm a posteriori error estimator for a control-constrained, linear-quadratic optimal control problem. The estimator yields optimal experimental rates of convergence within an adaptive loop.
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Taxonomy
TopicsAdvanced Numerical Methods in Computational Mathematics · Numerical methods in inverse problems · Nuclear reactor physics and engineering