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Maximum–norm a posteriori error estimates for an optimal control problem

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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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Acknowledgements

E. Otárola was supported in part by CONICYT through FONDECYT project 11180193. A. J. Salgado was supported in part by NSF Grant DMS-1418784. R. Rankin was supported in part by Universidad de Chile through BASAL PFB03 CMM project. The authors would like to thank Alejandro Allendes.

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Authors and Affiliations

  1. Departamento de Matemática, Universidad Técnica Federico Santa María, Valparaíso, Chile

    Enrique Otárola

  2. School of Mathematical Sciences, University of Nottingham Ningbo China, Ningbo, China

    Richard Rankin

  3. Department of Mathematics, University of Tennessee, Knoxville, TN, 37996, USA

    Abner J. Salgado

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  1. Enrique Otárola
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  2. Richard Rankin
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  3. Abner J. Salgado
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Correspondence to Richard Rankin.

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Otárola, E., Rankin, R. & Salgado, A.J. Maximum–norm a posteriori error estimates for an optimal control problem. Comput Optim Appl 73, 997–1017 (2019). https://doi.org/10.1007/s10589-019-00090-0

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