Application of bacteria foraging algorithm for the design optimization of multi-objective Yagi-Uda array

Abstract

The design of antenna array with desirable multiple performance parameters such as directivity, input impedance, beam width, and side-lobe level using any optimization algorithm is a highly challenging task. Bacteria Foraging Algorithm (BFA), as reported by electrical engineers, is the most robust and efficient algorithm in comparison with other presently available algorithms for global optimization of multi-objective, multi-parameter design problems. The objective of this article is to apply this new optimization technique, BFA, in the design of YagiUda array for multi-objective design parameters. We optimize length and spacing for 6 and 15 elements array to achieve higher directivity, pertinent input impedance, minimum 3-dB beam width, and maximum front to back ratio both in the E and H planes of the array. At first, we develop a Method of Moments code in MATLAB environment for the Yagi-Uda array structure for obtaining the above design parameters and then coupled with the BFA for the evaluation of the optimized design parameters. Detail simulation results are included to confirm the design criteria.

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“…The reason behind lower convergence time is due to the well sensing and cognitive capabilities of the bacteria and the time is not at all affected when the numbers of parameters to be optimized are many. Because of the advantages mentioned, the electrical engineering problems [21, 22] have been dealt with BFA for optimization as well as antenna design [12, 13]. From biological perspective, the term foraging can be treated as an optimizing process with the idea that the effort spent by the bacteria in seeking rich nutrient per unit time should be as low (minimum) as possible.…”

“…The convergence time, robustness, and precision are considered to be the inherent characteristics behind the selection of this optimization algorithm. BFA being a very strong and suitable algorithm for global optimization problem has recently been applied to design Yagi‐Uda [12] and Adaptive Antenna Arrays [13]. The reason of considering BFA over other optimization algorithm is clearly described in those papers [12, 13].…”

“…BFA being a very strong and suitable algorithm for global optimization problem has recently been applied to design Yagi‐Uda [12] and Adaptive Antenna Arrays [13]. The reason of considering BFA over other optimization algorithm is clearly described in those papers [12, 13]. Such design motivated us to explore the possibility of reviewing the design optimization aspect of LPDA in the light of BFA.…”

“…The biological aspects of BFA namely chemotaxis, swarming, reproduction, and elimination and dispersal [16] have been reflected in the computation of the minimum cost or fitness function [12] of the LPDA in terms of some predefined values for antenna performance parameters. For each performance parameter, there are 134 numbers of computations over 400 MHz BWs to receive 49 TV channels [17].…”

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“…BFA has been used to solve various types of engineering problems [19]- [21], such as motor efficiency calculation in field conditions by solving the equivalent circuit [22], [23]. However, in [22], only the positive-sequence circuit is considered, thus limiting its use to those cases in which the voltage is balanced; while in [23], the negative-and positive-sequence circuits of the fundamental component are considered, allowing analyzing unbalanced motors, but without harmonics.…”