Optimization of Resonant Frequency of Circular Patch Microstrip Antenna Using Particle Swarm Optimization

2011 ◽  
Author(s):  
Saurabh Kumar ◽  
Rajesh Kumar ◽  
B.K. Kanaujia
Keyword(s):  
Particle Swarm Optimization ◽  
Resonant Frequency ◽  
Microstrip Antenna ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Circular Patch

scholarly journals Metaheuristic Regression Equations for Split-Ring Resonator Using Time-Varying Particle Swarm Optimization Algorithm

Electronics ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 300
Author(s):  
Muhammad Mughal ◽  
Tahir Ejaz ◽  
Arshad ◽  
Ashiq Hussain
Keyword(s):  
Particle Swarm Optimization ◽  
Resonant Frequency ◽  
Quality Factor ◽  
Ring Resonator ◽  
Particle Swarm ◽  
Split Ring Resonator ◽  
Regression Equations ◽  
Time Varying ◽  
Split Ring ◽  
Swarm Optimization

This article presents a new technique for determining accurate values of resonant frequency and quality factor pertaining to the split-ring resonator. Different conducting shield materials have been used around a copper split-ring. The split-ring has been designed to operate at about 2.1 GHz. Various equations were worked out earlier to determine the values of resonant frequency and quality factor. However, these equations yielded different solutions. Therefore, simulations were used to obtain the values of the resonant frequency and quality factor of the split-ring resonator with different five-shield materials, using High-Frequency Structure Simulator (HFSS) software. In this work, a novel method has been introduced for obtaining values of resonant frequency which provides results with negligible error. An optimal technique, namely time-varying particle swarm optimization (TVPSO), was then performed to obtain two sets of equations for resonant frequency and quality factor. The two sets of equations, optimized using TVPSO, were compared for their effectiveness in matching the actual frequency and quality factor for each of the five materials. It was found that the TVPSO was significant in achieving the frequency and quality factor regression equation to accurately resemble the actual values portrayed by the low mean absolute error.

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