Application of adaptive neuro-fuzzy inference system technique in design of rectangular microstrip patch antennas
Abstract
The recent explosion in information technology and wireless communications has created many opportunities for enhancing the performance of existing signal transmission and processing systems and has provided a strong motivation for developing novel devices and systems. An indispensable element of any wireless communication system is the antenna. microstrip patch antenna (MPA) is well suited for wireless communication due to its light weight, low volume and low profile planar configuration which can be easily conformed to the host surface. In this paper, an adaptive neuro‐fuzzy inference systems (ANFIS) technique is used in design of MPA. This artificial Intelligence (AI) technique is used in determining the parameters used in the design of a rectangular microstrip patch antenna. The ANFIS has the advantages of expert knowledge of fuzzy inference system (FIS) and the learning capability of artificial neural network (ANN). By determining the patch dimensions and the feed point of a rectangular microstrip antenna, this paper shows that ANFIS produces good results that are in agreement with Antenna Magus simulation results.
Key words: Artificial intelligence (AI), microstrip patch antennas (MPAs), adaptive neuro‐fuzzy inference system (ANFIS)
Open access articles published in the Journal of Agriculture, Science and Technology are under the terms of the Creative Commons Attribution (CC BY) License which permits use, distribution and reproduction in any medium, provided the original work is properly cited. The CC BY license permits commercial and non-commercial re-use of an open-access article, as long as the author is properly attributed.
Copyright on any research article published in the Journal of Agriculture, Science and Technology is retained by the author(s). The authors grant the Journal of Agriculture, Science and Technology with a license to publish the article and identify itself as the original publisher. Authors also grant any third party the right to use the article freely as long as its original authors, citation details and publisher are identified.
Use of the article in whole or in part in any medium requires proper citation as follows:
Title of Article, Names of the Author, Year of Publication, Journal Title, Volume (Issue) and page. Links to the final article on the JSRE website are encouraged.
The Creative Commons Attribution License does not affect any other rights held by authors or third parties in the article, including without limitation the rights of privacy and publicity. Use of the article must not assert or imply, whether implicitly or explicitly, any connection with, endorsement or sponsorship of such use by the author, publisher or any other party associated with the article.
For any reuse or distribution, users must include the copyright notice and make clear to others that the article is made available under a Creative Commons Attribution license, linking to the relevant Creative Commons web page. Users may impose no restrictions on the use of the article other than those imposed by the Creative Commons Attribution license.
To the fullest extent permitted by applicable law, the article is made available as is and without representation or warranties of any kind whether express, implied, statutory or otherwise and including, without limitation, warranties of title, merchantability, fitness for a particular purpose, non-infringement, absence of defects, accuracy, or the presence or absence of errors.