Optimum Design of Antennas Using Metamaterials with the Efficient Global Optimization (EGO) Algorithm

被引：1
|
作者：
Southall, Hugh L. [1 ]
O'Donnell, Terry H. [1 ]
Derov, John S. [1 ]
机构：
[1] USAF, Res Lab, Hanscom AFB, MA 01731 USA
来源：
EVOLUTIONARY AND BIO-INSPIRED COMPUTATION: THEORY AND APPLICATIONS IV | 2010年 / 7704卷
关键词：
Efficient global optimization (EGO); computational electromagnetics (CEM); evolutionary computation; antenna design optimization; design and analysis of computer experiments (DACE); metamaterials; folded triangular bowtie antenna (FTBA) element; wideband antenna elements; low profile antennas; WIDE-BAND;
D O I：
10.1117/12.851794
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
EGO is an evolutionary, data-adaptive algorithm which can be useful for optimization problems with expensive cost functions. Many antenna design problems qualify since complex computational electromagnetics (CEM) simulations can take significant resources. This makes evolutionary algorithms such as genetic algorithms (GA) or particle swarm optimization (PSO) problematic since iterations of large populations are required. In this paper we discuss multi-parameter optimization of a wideband, single-element antenna over a metamaterial ground plane and the interfacing of EGO (optimization) with a full-wave CEM simulation (cost function evaluation).
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页数：10
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