The Research Of Chaos Boolean Particle Swarm Optimization Algorithm And Its Application In The Photonic Crystal Antenna Design

The intelligence algorithm is based on the theory of evolution, which belongs to the emerging discipline of modern science and technology. In other word, with the characteristics of self-organizing and adaptability, it simulates evolutionary processes and mechanisms in different angles. At present, the intelligence algorithm is utilized to optimize and design antennas automatically, which has become more and more popular. Particle Swarm Optimization (PSO), studied in this paper, a typical evolutionary computation technique. Usually, it is simple in structure and easy to be realized. Also, Strong robustness and fast convergence are its advantage. Nowadays, PSO has been widely applied in every field, such as, circuit optimization, dynamic problem, function optimization and neural network training etc.Photonic Crystals or Photonic Band-gap (PBG) structures, as posed by the optical field, are arranged periodically medium or metal structure, belonging to the category of the periodic metal-dielectric material with a frequency band-gap. Usually, we claim that the research of PBG structures is mainly photonic band gaps so that we can put use of the photonic band gaps in the application.This paper is mainly about the characteristics of forbidden band and its application. We can design a photonic crystal microstrip antenna that the dielectric substrate is a two-dimensional photonic crystal structure. And the designed microstrip antenna based on the optimal photonic crystal has a large band gap. On the other hand, we should make the working frequency left in the forbidden band.In this paper, the basic idea of Boolean PSO is introduced. In order to obtain a good output, Chaotic optimization algorithm and Boolean algorithm are adopted to improve PSO. In a word, a new hybrid Chaotic Boolean Particle Swarm Optimization (CBPSO) is finally proposed and applied in the photonic crystal microstrip antenna designs. Specifically, two sections are included just as follow:(A) Chaotic Boolean Particle Swarm Optimization. Against the insufficient diversity of Boolean PSO, we have proposed CBPSO by introducing chaotic optimization algorithm. Through numerical algorithm testing problem, come to the conclusion that the algorithm converges fast and high accuracy. CBPSO has improved algorithm premature characteristic and avoid algorithm falls into local optimum.(B) Optimal design of photonic crystal microstrip antenna. In simulation software HFSS, CBPSO algorithm as the optimization tool, used to design photonic crystal microstrip antenna. Implement the design of photonic crystal microstrip antennas with different structure and different size of the original cell. Complete design of photonic crystals antenna array.