Adaptive Neuro Fuzzy Inference System For Analysis And Design Of Microstrip Antenna

Abstract

newline newline In the challenging scenario of wireless communication, everywhere the demands of microstrip patch antenna have become a major research topic. They have many more advantages like low cost, low profile, light weight, ease of fabrication and compatible with monolithic microwave integrated circuit design etc. However, they have some short comings too. Major of which is their narrow bandwidth and low gain. So that for a particular application patch should be analyses accurately. Hence, the physical dimensions and substrate material have to be precisely predicted and for impedance matching, the feed location has to be appropriately chosen. Thus, there is an emergent demand on use of Computer Aided Design CAD model for antenna design engineers. In past decades in the designing of traditional microstrip antenna the analysis techniques such as cavity model and transmission line model were generally used. Although the complicated shapes of antennas cannot be analyzed with these traditional techniques. Consequently some other powerful techniques such as method of moment and finite difference time domain method were used. But these techniques, involves rigorous mathematical formulation with extensive numerical procedure thus, more time consuming. Nowadays most powerful simulation software such as IE3D, HFSS and CST microwave studio etc. are commonly used for analysis of complex type of antenna and other microwave design structure. This simulation software perform results with trial and error basis. All these restrictions have forced to develop an efficient optimizing soft computing tool for accurate and competent antenna design. In this thesis ANN and ANFIS analysis techniques are mainly focused to analysis and design of novel and complex microstrip patch antennas. newline