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Sensitivity analysis approach for reduced-order approximations of optimal control problems governed by Burgers equation
Date
2016-12-01
Author
Akman, Tuğba
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The reduced-order model of the optimal control problem governed by Burgers equation is derived using the proper orthogonal decomposition (POD) method. The reduced-order solution depending on parameters, which are different from the nominal values, may not be accurate if the POD basis functions depending on the nominal values are used to derive the reduced-order model. It is known that Burgers equation is sensitive to the perturbations in the diffusion term, so we use the sensitivity information to improve the robustness of the POD solution by generating two new bases: extrapolated and expanded POD basis. We compare these different bases in terms of accuracy, robustness, and computational time. Copyright (c) 2015 John Wiley & Sons, Ltd.
Subject Keywords
Control and Systems Engineering
,
Software
,
Control and Optimization
,
Applied Mathematics
URI
https://hdl.handle.net/11511/62333
Journal
OPTIMAL CONTROL APPLICATIONS & METHODS
DOI
https://doi.org/10.1002/oca.2230
Collections
Department of Mathematics, Article
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T. Akman, “Sensitivity analysis approach for reduced-order approximations of optimal control problems governed by Burgers equation,”
OPTIMAL CONTROL APPLICATIONS & METHODS
, pp. 1175–1192, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/62333.