Particle Swarm Optimization with Aging Leader and Challengers (ALC-PSO) method, which represents a novel approach for optimization problems, is applied for radiation pattern synthesis of a three ring concentric Ellipt...
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ISBN:
(纸本)9781467385497
Particle Swarm Optimization with Aging Leader and Challengers (ALC-PSO) method, which represents a novel approach for optimization problems, is applied for radiation pattern synthesis of a three ring concentric elliptical array Antenna (CEA) of isotropic elements which can generate beam pattern with maximum reduced Side Lobe Level (SLL). This paper introduces a recently developed metaheuristic algorithm, known as ALC-PSO, to the pattern synthesis of recently proposed configured planar array, CEA, with desired SLL by amplitude-only optimization. To overcome the problem of premature convergence characteristic of PSO, ALC-PSO is designed without significantly impairing the fast converging property of PSO. To improve the radiation pattern in terms of minimum relative SLL, a set of antenna designed parameters as excitation weights of the elements and eccentricity of the elliptical shaped rings are to be developed. The variation of SLL with eccentricity of synthesized array is also reported. Compare with conventional PSO method, ALC-PSO outperform with the goal of maximum SLL suppression.
In this paper, optimal design of single-ring and multi-ring circular array, hexagonal array, and ellipticalarray of isotropic antenna has been carried out using Simplex Particle Swarm Optimization (Simplex-PSO). The ...
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In this paper, optimal design of single-ring and multi-ring circular array, hexagonal array, and ellipticalarray of isotropic antenna has been carried out using Simplex Particle Swarm Optimization (Simplex-PSO). The synthesis of the array geometry is first formulated as an optimization problem with the goal of side lobe level reduction and is then solved using Simplex-PSO algorithm for optimum current excitations. To overcome the premature convergence characteristic of PSO, Simplex-PSO is considered while preserving the fast converging property of PSO. Two design examples are presented which illustrate the effectiveness of Simplex-PSO algorithm, and the optimization goal for each example is easily achieved. The design results obtained using Simplex-PSO are superior to those obtained using popular algorithms like PSO and its variant craziness-based PSO (CRPSO) and PSO with aging leader and challengers (ALC-PSO) in a statistically significant way.
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