Metaheuristic Optimization Algorithms of Swarm Intelligence in Patch Antenna Design

Paola M. Guaman, L. F. Guerrero-Vásquez, J. P. Bermeo, Paul A. Chasi
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引用次数: 5

Abstract

The patch antennas are widely used today and the research about their design is very important due to the numerous communication systems in which they are used. However, for these applications is essential that their parameters are suitable. Besides, the theoretical design of this type of antennas is not always effective. So, the metaheuristic optimization algorithms combined with simulations are presented, as a very efficient tool for the design of this class of antennas. Swarm intelligence is imitated of organisms present in nature that have an organization to each other and this communication between members of the same population makes it possible to find a global optimum value of the parameters. In this paper, metaheuristic swarm intelligence optimization algorithms have been used for the design of patch antennas. The optimization techniques used were particle swarm optimization, firefly algorithm and directional bat algorithm. The optimization of the operating frequency, the reflection parameter or Sl l and the impedance of the antenna is performed. Each algorithm performs the search in a different way. Finally, the results obtained are presented.
贴片天线设计中的群智能元启发式优化算法
贴片天线在当今的通信系统中得到了广泛的应用,因此对其设计的研究具有十分重要的意义。然而,对于这些应用来说,它们的参数是否合适是至关重要的。此外,这类天线的理论设计并不总是有效的。因此,本文提出了结合仿真的元启发式优化算法,为该类天线的设计提供了一个非常有效的工具。群体智能是模仿自然界中存在的生物体,它们彼此之间有一个组织,同一种群成员之间的这种交流使得找到参数的全局最优值成为可能。本文将元启发式群智能优化算法应用于贴片天线的设计。优化技术主要有粒子群算法、萤火虫算法和定向蝙蝠算法。对天线的工作频率、反射参数Sl和阻抗进行了优化。每种算法都以不同的方式执行搜索。最后给出了计算结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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