Tunable Frequency Selective Surface Design Using Automated Random Optimization

Abstract

We present an automated approach to design a high performance, tunable frequency selective surface (FSS). The main goal of this study is to provide the simultaneous optimization of the FSS structure in two states of the 4 incorporated varactors, aiming to get an acceptable polarization filtering and polarization control. Generally, microwave designs are dealing with a large amount of data and they depend on the engineer's experiences. In order to get rid of this dependency and providing a ready-to-fabricate layout, we propose an optimization-oriented method based on the random optimization (RO). The RO method is applied in an automated environment where HFSS and Matlab are collaborating together forming a co-simulation platform where the design parameters are optimized up to achieve suitable output performances.