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Computationally-efficient design optimisation of antennas by accelerated gradient search with sensitivity and design change monitoring

Abstract

Electromagnetic (EM) simulation tools are of primary importance in the design of contemporary antennas. The necessity of accurate performance evaluation of complex structures is a reason why the final tuning of antenna dimensions, aimed at improvement of electrical and field characteristics, needs to be based on EM analysis. Design automation is highly desirable and can be achieved by coupling EM solvers with numerical optimisation routines. Unfortunately, its computational overhead may be impractically high for conventional algorithms. This study proposes an efficient gradient search algorithm with numerical derivatives. The acceleration of the optimisation process is obtained by means of the two mechanisms developed to suppress some of finite-differentiation-based updates of the antenna response sensitivities that involve monitoring and quantifying the gradient changes as well as design relocation between the consecutive algorithm iterations. Both methods considerably reduce the need for finite differentiation, leading to significant computational savings. At the same time, excellent reliability and repeatability is maintained, which is demonstrated through statistics over multiple algorithm runs with random initial designs. The proposed approach is validated using a benchmark set of wideband antennas. The proposed algorithm is competitive to both the reference trust-region algorithm as well as its recently reported accelerated versions.

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Category:
Articles
Type:
artykuły w czasopismach
Published in:
IET Microwaves Antennas & Propagation no. 14, pages 165 - 170,
ISSN: 1751-8725
Language:
English
Publication year:
2020
Bibliographic description:
Pietrenko-Dąbrowska A., Kozieł S.: Computationally-efficient design optimisation of antennas by accelerated gradient search with sensitivity and design change monitoring// IET Microwaves Antennas & Propagation -Vol. 14,iss. 2 (2020), s.165-170
DOI:
Digital Object Identifier (open in new tab) 10.1049/iet-map.2019.0358
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