Robust optimization utilizing the second-order design sensitivity information
Robust optimization utilizing the second-order design sensitivity information
This paper presents an effective methodology for robust optimization of electromagnetic devices. To achieve the goal, the method improves the robustness of the minimum of the objective function chosen as a design solution by minimizing the second-order sensitivity information, called a gradient index (GI) and defined by a function of gradients of performance functions with respect to uncertain variables. The constraint feasibility is also enhanced by adding a GI corresponding to the constraint value. The distinctive feature of the method is that it requires neither statistical information on design variables nor calculation of the performance reliability during the robust optimization process. The validity of the proposed method is tested with the TEAM Workshop Problem 22
optimization, robust optimization, sensitivity analysis
3117-3120
Kim, Nam-Kyung
bf59c1a7-a705-40e1-94fd-ba195df3e06f
Kim, Dong-Hun
a320b5a0-1b03-45df-8564-2b7b61a776b0
Kim, Dong-Wook
252df2be-3037-413e-865e-03bffdcfacea
Kim, Heung-Geun
99ce1213-8bde-41cc-a9b1-495be6ec97e8
Lowther, D.A.
cfcdbf42-4450-4742-b6b7-591d16adfdda
Sykulski, J.K.
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb
August 2010
Kim, Nam-Kyung
bf59c1a7-a705-40e1-94fd-ba195df3e06f
Kim, Dong-Hun
a320b5a0-1b03-45df-8564-2b7b61a776b0
Kim, Dong-Wook
252df2be-3037-413e-865e-03bffdcfacea
Kim, Heung-Geun
99ce1213-8bde-41cc-a9b1-495be6ec97e8
Lowther, D.A.
cfcdbf42-4450-4742-b6b7-591d16adfdda
Sykulski, J.K.
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb
Kim, Nam-Kyung, Kim, Dong-Hun, Kim, Dong-Wook, Kim, Heung-Geun, Lowther, D.A. and Sykulski, J.K.
(2010)
Robust optimization utilizing the second-order design sensitivity information.
IEEE Transactions on Magnetics, 46 (8), .
(doi:10.1109/TMAG.2010.2043719).
Abstract
This paper presents an effective methodology for robust optimization of electromagnetic devices. To achieve the goal, the method improves the robustness of the minimum of the objective function chosen as a design solution by minimizing the second-order sensitivity information, called a gradient index (GI) and defined by a function of gradients of performance functions with respect to uncertain variables. The constraint feasibility is also enhanced by adding a GI corresponding to the constraint value. The distinctive feature of the method is that it requires neither statistical information on design variables nor calculation of the performance reliability during the robust optimization process. The validity of the proposed method is tested with the TEAM Workshop Problem 22
Text
IEEE_Mag_v46n8_2010_p3117.pdf
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Published date: August 2010
Keywords:
optimization, robust optimization, sensitivity analysis
Organisations:
EEE
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Local EPrints ID: 271462
URI: http://eprints.soton.ac.uk/id/eprint/271462
ISSN: 0018-9464
PURE UUID: 5a290b7a-7ce2-43e7-bd30-48ec077b78c0
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Date deposited: 05 Aug 2010 15:39
Last modified: 15 Mar 2024 02:34
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Contributors
Author:
Nam-Kyung Kim
Author:
Dong-Hun Kim
Author:
Dong-Wook Kim
Author:
Heung-Geun Kim
Author:
D.A. Lowther
Author:
J.K. Sykulski
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