Optimal design of Fractional Order Digital Integrators – An Evolutionary Approach

Mahata, Shibendu; SAHA, Suman Kumar; KAR, Rajib; MANDAL, Durbadal

doi:10.24200/sci.2017.4405

Cited by 2 publications

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References 23 publications

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“…Hence, the CF minimization signifies the maximum reduction of SLL as well as FNBW value. A lot of researchs have already been done for the optimal radiation pattern synthesis of CAA using different optimization techniques [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34]. But, in this paper, GWO algorithm is employed to optimize the current excitation weights and inter-element spacing among the array elements of the CDAA for the maximum reduction of CF value.…”

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confidence: 99%

An Optimal Radiation Pattern Synthesis and Correction of Mutually Coupled Circular Dipole Antenna Array

2020

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This paper proposes a fundamental approach for radiation pattern correction of the mutually coupled circular dipole antenna array (CDAA) using parametric assimilation technique. The effect of mutual coupling is an indispensable part of any practical design issue of the antenna array. Many analytical and numerical techniques have been put forward in the past few decades for the calculation, compensation and reduction of mutual coupling effect. This paper shows an accurate method for mutual coupling correction by using a recently proposed technique called parametric assimilation technique, where the values of mutual impedance are calculated and assimilated with the values of the desired radiation pattern. The proposed technique is cost-effective, less complicated and easy to implement while achieves better performance for mutually coupled circular dipole antenna array synthesis. Grey Wolf Optimization (GWO) algorithm is a state-of-the-art stochastic algorithm applied here to find the optimal values of the current excitation weights and the inter-element spacing between each element of the CDAA for the desired, uncorrected and corrected far-field radiation pattern synthesis. PSO and DE optimization-based statistical results are also reported to compare the results obtained by using GWO algorithm to confirm the outstanding performance of GWO algorithm based design.

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