Hybrid Method of Artificial Neural Network and Simulated Annealing Algorithm for Optimizing Wideband Patch Antennas
Yejun He, Jinhua Huang, Wenting Li, Long Zhang, Sai‐Wai Wong, Zhi Ning Chen
Abstract
In order to design the wideband patch antenna, a hybrid method based on the artificial neural network (ANN) and the simulated annealing (SA) algorithm is proposed in this communication. The ANN is employed to describe the nonlinear relationship between the geometric parameters and the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$S$ </tex-math></inline-formula> -parameters of the antenna. The ANN is trained by the dataset obtained from the high-frequency structure simulator (HFSS). More importantly, the dataset is divided into three groups according to their own characteristics so that the ANN can be trained faster and better. The SA is employed to broaden the bandwidth of the patch antenna with the required center frequency. Then three wideband patch antennas with different center frequencies are designed to demonstrate the feasibility of the proposed method. Several slots are added to the patch to achieve the wide bandwidth. The results prove that the proposed method can obtain the wideband patch antenna quickly and efficiently.