Fractal Antenna Design using Bio-inspired Computing Algorithms

Development of Hybrid Bio-inspired Computing Algorithms for Design of Fractal Antennas

Author(s): Balwinder S. Dhaliwal*, Suman Pattnaik* and Shyam Sundar Pattnaik *

Pp: 106-133 (28)

DOI: 10.2174/9789815136357123010008

* (Excluding Mailing and Handling)


One of the novel contributions of this book is the development of hybrid bio-inspired computing algorithms for the design of fractal antennas. This work is presented in this chapter. The hybrid algorithms are developed to design the proposed fractal antennas for desired frequencies. The performance comparison of bio-inspired computing algorithms for the design of a multiband Sierpinski Gasket fractal antenna is also explained. The development of various hybrid algorithms like the GA-ANN hybrid Algorithm, BFO-ANN ensemble hybrid Algorithm, and PSO-ANN Ensemble hybrid Algorithm is explained. The use of ANN models as objective functions of optimization algorithms is discussed in this chapter. This chapter also deals with the experimental testing and validation of the developed fractal antennas. The photographs of the fabricated antennas and the experimental results are included. The comparison of the simulated results and experimental results is discussed. The suitability of the designed antennas for different applications is also highlighted in this chapter. 

Keywords: Bacterial foraging optimization, Crown fractal antenna, Fractal antenna, Genetic algorithms, Miniaturized antenna, Particle swarm optimization, Sierpinski gasket.

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