Artificial intelligence using Nelder-Mead algorithm- based design and performance optimization of microstrip patch antenna

Abstract

Artificial intelligence systems are one of the important machines in performing operations that are difficult to perform traditionally. Optimization is one of the difficult and delicate processes that AI can be used to accomplish, especially if the optimizations are too small for antennas like microstrip patch antenna. A Microstrip patch antenna is considered one of the most widely used antennas that vary from lightweight wireless devices to airplanes and airspaces applications. One of the most attractive points about those antennas is their lightweight, small size, and ease of fabrication process. Although this antenna has many advantages, it suffers from some drawbacks like low gain and limited bandwidth. In this paper, we are presenting an optimization process by using the Nelder-Mead algorithm to achieve a new design of patch antenna that offers a broader bandwidth and higher gain. This design is achieved by optimizing the dimensions of the width and the frequency of the antenna. The results show that this device is responding perfectly at 1.471GHz and the ranges of substrate dimensions and relative permittivity affect the device performance and behavior.