Optimal design of frequency selective surfaces with fractal motifs

• Published in: IET microwaves, antennas & propagation Vol. 8; no. 9; pp. 627 - 631
• Main Authors: Silva, Marcelo Ribeiro da, Nóbrega, Clarissa de Lucena, Silva, Paulo Henrique da F, D'Assunção, Adaildo Gomes
• Format: Journal Article
• Language: English
• Published: Stevenage The Institution of Engineering and Technology 01.06.2014; Institution of Engineering and Technology; The Institution of Engineering & Technology
• Subjects: Algorithms; alternative electromagnetic optimisation technique; Applied sciences; bees algorithm; Circuit properties; computational intelligence tools; Computer simulation; continuous genetic algorithm; Design engineering; Diffraction, scattering, reflection; Electric, optical and optoelectronic circuits; electrical engineering computing; Electronic circuits; Electronics; Exact sciences and technology; Fractal analysis; Fractals; Frequency filters; Frequency selective surfaces; frequency selective surfaces optimal design; FSS band‐stop spatial fllter; FSS parametric full‐wave analysis; genetic algorithms; Mathematical models; multilayer perceptrons; neural network model; Optimization; particle swarm optimisation; population‐based search algorithm simulations; Radiocommunications; Radiowave propagation; repetitive cost function computations; search problems; spatial filters; Telecommunications; Telecommunications and information theory; Vicsek fractal motif; electrical engineering computing; multilayer perceptrons; frequency selective surfaces; alternative electromagnetic optimisation technique; particle swarm optimisation; FSS band-stop spatial fllter; population-based search algorithm simulations; bees algorithm; genetic algorithms; FSS parametric full-wave analysis; spatial filters; computational intelligence tools; continuous genetic algorithm; neural network model; frequency selective surfaces optimal design; search problems; Vicsek fractal motif; repetitive cost function computations; Performance evaluation; Frequency selective surfaces; Electromagnetism; Prototype; Parametric analysis; Evolutionary algorithm; Neural network; Computational complexity; Particle swarm optimization; Search algorithm; Optimal design; Fractal; Biomimetics; Simulation; Genetic algorithm; Resonance frequency; Multilayer perceptrons; Cost function; Band stop filter; Artificial intelligence; Numerical convergence
• ISSN: 1751-8725; 1751-8733; 1751-8733
• DOI: 10.1049/iet-map.2013.0462

An alternative electromagnetic (EM) optimisation technique for the optimal design of frequency selective surfaces (FSSs) with fractal motifs is described. Based on computational intelligence tools, the proposed technique overcomes the high computational cost associated with FSS parametric full-wave analysis. In an application example, a fast and accurate multilayer perceptrons model of a FSS band-stop spatial filter with a Vicsek fractal motif is developed. This neural network model is used for repetitive cost function computations in population-based search algorithm simulations. A bees algorithm, continuous genetic algorithm and particle swarm optimisation are used for FSS optimisation with specific resonant frequency and bandwidth. The performance of these algorithms is compared in terms of numerical convergence. Consistent results are presented for a second-pass of designed FSS prototype with Vicsek fractal elements.