Back close

Optimization of ring parameters of artificial magnetic resonators using Swarm intelligence and Hybrid Genetic Algorithm

Publication Type : Conference Paper

Publisher : IEEE

Source : Electronics Computer Technology (ICECT), 2011 3rd International Conference on, IEEE, Volume 2, Kanyakumari, p.316-321 (2011)

Url : http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5941709

Keywords : Ansoft HFSS, artificial magnetic resonators, constrained nonlinear optimization hybrid, Convergence, dynamic electromagnetic environment, Electromagnetic compatibility, Electromagnetic shielding, electromagnetic shielding devices, equivalent circuit, Equivalent circuits, Genetic Algorithm(GA), Genetic algorithms, hybrid genetic algorithm, Integrated circuit modeling, labyrinth resonator, Labyrinth Resonator (LR), Metamaterials, multiple split ring resonator, Multiple Split Ring Resonator (MSRR), Negative permeability, Optimization, particle swarm optimisation, particle swarm optimization, Particle Swarm Optimization(PSO), Resonant frequency, Resonators, ring parameters, Sequential Quadratic Programming (SQP), spiral resonator, Spiral Resonator (SR), Spirals, Swarm Intelligence, wireless technology

Campus : Coimbatore

School : School of Engineering

Department : Electronics and Communication

Year : 2011

Abstract : Proliferation of wireless technology has made Electromagnetic Compatibility an indispensable field of research. The need for efficient system performance in a dynamic electromagnetic environment calls for accurate design of Electromagnetic shielding devices. Artificial magnetic resonators are miniature structures with negative permeability within a specific band. These resonators act as narrowband absorbers at wavelengths in the order of their dimensions. In this paper, the existing equivalent circuit models are discussed for three kinds of magnetic resonators: Multiple Split Ring Resonator, Spiral Resonator, and Labyrinth Resonator. The dependence of the resonant frequency on multiple geometric parameters of the rings is demonstrated. The design parameters of the rings are optimized using Particle Swarm Optimization (PSO) and the proposed Genetic Algorithm - Constrained Nonlinear Optimization Hybrid. These results have been supported by full wave simulations using Ansoft HFSS.

Cite this Research Publication : D. Karthik, Sreenivas, V. N., and Dr. Shanmugha Sundaram G. A., “Optimization of ring parameters of artificial magnetic resonators using Swarm intelligence and Hybrid Genetic Algorithm”, in Electronics Computer Technology (ICECT), 2011 3rd International Conference on, Kanyakumari, 2011, vol. 2, pp. 316-321.

Admissions Apply Now