GA Analysis of Switchability of Ferrite Rectangular Patch Antenna

Abstract

The application of Genetic Algorithm (GA) to analyze / optimize the switching behavior of magnetically biased switchable microstrip antenna, fabricated on ferrite substrate, is reported. In this work, GA has been applied to optimize extraordinary wave propagation constant (Ke) which is mainly responsible for the switchability of antenna. The wave propagation constant becomes zero or negative under proper magnetic biasing which resist the antenna as radiator without a mechanical maneuvering. The fitness functions for the GA program have been developed using mathematical formulation based on nonreciprocal approach of ferrite substrate under external magnetic field. The computed results are in good agreement with the results obtained experimentally and trained artificial neural network analysis. In this ANN training Radial Basis Function (RBF) networks is used. All programming related to genetic algorithm and ANN analysis performed by MatLab 7.1.