A new chaotic teaching learning based optimization for frequency reconfigurable antennas design

Article type: Research Article

Authors: Zadehparizi, Fatemeh | Jam, Shahrokh^{; *}

Affiliations: Department of Electrical and Electronic Engineering, Shiraz University of Technology, Shiraz, Iran

Correspondence: [*] Corresponding author. Shahrokh Jam, Department of Electrical and Electronic Engineering, Shiraz 71555-313, Iran. E-mail: [email protected].

Abstract: In this paper, a new chaotic teaching learning based optimization (CTLBO) is proposed. TLBO is a rather newly proposed population-based algorithm. This algorithm has no control parameters for the tuning and has a simple structure. We improve its performance by chaotic maps. First, the presented CTLBO is tested on nine unimodal/multimodal benchmark functions. Then, chaotic sequences are applied as vectors with different initial values for design of a frequency reconfigurable antenna (FRA) as a practical example. Comparisons of the performance of this algorithm with those of the basic TLBO, genetic algorithm and particle swarm optimization show the ability of this algorithm in design of FRAs in terms of faster convergence and better performance. A prototype of the optimized antenna with CTLBO algorithm is fabricated and the simulation and measurement results agree suitably.

Keywords: Teaching learning based optimization, Chaos theory, Frequency reconfigurable antenna.

DOI: 10.3233/JIFS-171420

Journal: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1353-1360, 2019