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Computational methods for boundary optimal control and identification problems
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SYSNO ASEP 0543695 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Computational methods for boundary optimal control and identification problems Author(s) Axelsson, Owe (UGN-S) RID
Béreš, Michal (UGN-S) ORCID, RID, SAI
Blaheta, Radim (UGN-S) RID, SAI, ORCIDNumber of authors 3 Source Title Mathematics and Computers in Simulation. - : Elsevier - ISSN 0378-4754
Roč. 189, November 2021 (2021), s. 276-290Number of pages 15 s. Publication form Online - E Language eng - English Country NL - Netherlands Keywords parameter identification ; optimal control ; iterative solution ; preconditioning Subject RIV BA - General Mathematics OECD category Applied mathematics R&D Projects LQ1602 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) Method of publishing Limited access Institutional support UGN-S - RVO:68145535 UT WOS 000683684700019 EID SCOPUS 85102641809 DOI 10.1016/j.matcom.2021.02.019 Annotation The paper deals with boundary optimal control methods for partial differential equation (PDE) problems with both target and control variables on specified parts of the boundary of the problem domain. Besides the standard aim in approximation of the target variable the paper also addresses an inverse identification of conditions on an inaccessible part of the boundary by letting them play the role of a control variable function and by overimposing boundary conditions at another part of the boundary of the given domain. The paper shows the mathematical formulation of the problem, the arising (regularized) Karush–Kuhn–Tucker (KKT) system and introduces preconditioners for the solution of the regularized system. The spectral analysis of the preconditioner, analysis of the approximation of the target function and boundary condition on an inaccessible part of the boundary and numerical tests with the proposed preconditioning techniques are included. Workplace Institute of Geonics Contact Lucie Gurková, lucie.gurkova@ugn.cas.cz, Tel.: 596 979 354 Year of Publishing 2022 Electronic address https://www.sciencedirect.com/science/article/pii/S0378475421000586
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