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Robust design optimisation of electromagnetic devices exploiting gradient indices and Kriging

Robust design optimisation of electromagnetic devices exploiting gradient indices and Kriging
Robust design optimisation of electromagnetic devices exploiting gradient indices and Kriging
Since uncertainties in variables are unavoidable, an optimal solution must consider the robustness of the design. The gradient index approach provides a convenient way to evaluate the robustness but is inconclusive when several possible solutions exist. To overcome this limitation, a novel methodology based on the use of first- and second-order gradient indices is proposed introducing the notion of gradient sensitivity. The sensitivity affords a measure of the change in the objective function with respect to the uncertainty of the variables. A Kriging method assisted by algorithms exploiting the concept of rewards is employed to facilitate function predictions for the robust optimisation process. The performance of the proposed algorithm is assessed through a series of numerical experiments. A modification to the correlation model through the introduction of a Kriging predictor and mean square error criterion allows efficient solution of large scale and multi-parameter problems. The three parameter version of TEAM Workshop Problem 22 has been used for illustration.
1751-8822
400-409
Xiao, Song
6ffa9657-513e-4b86-86a2-e560d3c09c72
Rotaru, Mihai
c53c5038-2fed-4ace-8fad-9f95d4c95b7e
Sykulski, Jan
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb
Xiao, Song
6ffa9657-513e-4b86-86a2-e560d3c09c72
Rotaru, Mihai
c53c5038-2fed-4ace-8fad-9f95d4c95b7e
Sykulski, Jan
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb

Xiao, Song, Rotaru, Mihai and Sykulski, Jan (2015) Robust design optimisation of electromagnetic devices exploiting gradient indices and Kriging. IET Science, Measurement & Technology, 9 (4), 400-409. (doi:10.1049/iet-smt.2014.0054).

Record type: Article

Abstract

Since uncertainties in variables are unavoidable, an optimal solution must consider the robustness of the design. The gradient index approach provides a convenient way to evaluate the robustness but is inconclusive when several possible solutions exist. To overcome this limitation, a novel methodology based on the use of first- and second-order gradient indices is proposed introducing the notion of gradient sensitivity. The sensitivity affords a measure of the change in the objective function with respect to the uncertainty of the variables. A Kriging method assisted by algorithms exploiting the concept of rewards is employed to facilitate function predictions for the robust optimisation process. The performance of the proposed algorithm is assessed through a series of numerical experiments. A modification to the correlation model through the introduction of a Kriging predictor and mean square error criterion allows efficient solution of large scale and multi-parameter problems. The three parameter version of TEAM Workshop Problem 22 has been used for illustration.

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Accepted/In Press date: 1 August 2014
Published date: 2 July 2015
Organisations: EEE

Identifiers

Local EPrints ID: 401299
URI: http://eprints.soton.ac.uk/id/eprint/401299
ISSN: 1751-8822
PURE UUID: aa881f9e-b42b-402b-9285-cd4a41514979
ORCID for Jan Sykulski: ORCID iD orcid.org/0000-0001-6392-126X

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Date deposited: 07 Oct 2016 11:41
Last modified: 20 Jul 2019 01:28

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