Surrogate-assisted optimization of 3D printed ceramic nonuniform nonplanar microstrip filter

Abstract

Herein, by using 3D printing technology and data-driven surrogate model-assisted optimization method, design of a ceramic material-based nonuniform nonplanar microstrip filter is taken into the consideration in a computationally efficient and low-cost manner. For this aim, 3D EM model of the proposed design had been used for generating training and validation data sets. Then commonly used state-of-the-art regression algorithms had been used for creating accurate and fast surrogate models to create a mapping between inputs of the model and outputs of the unit element design. After that, Grey Wolf Optimization algorithm had been used for design optimization of a bandpass filter. Then, via the use of 3D printer, the optimally designed filter had been prototyped and its performance characteristics are measured. As a result, by using 3D printer technology, ceramic material, and the proposed method, design optimization of nonuniform nonplanar microstrip filter can be achieved in a computationally efficient way.