Multi-species particle swarms optimization based on orthogonal learning and its application for optimal design of a butterfly-shaped patch antenna

Abstract

A new multi-species particle swarm optimization with a two-level hierarchical topology and the orthogonal learning strategy (OMSPSO) is proposed, which enhances the global search ability of particles and increases their convergence rates. The numerical results on 10 benchmark functions demonstrated the effectiveness of our proposed algorithm. Then, the proposed algorithm is presented to design a butterfly-shaped microstrip patch antenna. Combined with the HFSS solver, a butterfly-shaped patch antenna with a bandwidth of about 40.1% is designed by using the proposed OMSPSO. The return loss of the butterfly-shaped antenna is greater than 10 dB between 4.15 and 6.36 GHz. The antenna can serve simultaneously for the high-speed wireless computer networks (5.15–5.35 GHz) and the RFID systems (5.8 GHz).

Keywords

particle swarm optimization (PSO) / multi-species coevolution / orthogonal experimental design / butterfly-shaped patch antenna

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