Adaptive Feature Zero Assisted Surrogate-Based EM Optimization for Microwave Filter Design

Abstract

Feature-based electromagnetic (EM) optimization techniques can help avoid local minima in microwave design. Zeros of the transfer functions are recently used to help extract the features when the features of filter responses are not explicitly identifiable. This letter proposes a feature zero-adaptation approach to enlarge the surrogate range by overcoming the problem of varying orders of the transfer function w.r.t. the changes in design variables. In this way, the proposed technique allows larger step sizes for optimization, therefore, speeding up the overall EM optimization process. During each optimization iteration, parallel techniques are proposed to be used to generate multiple EM geometrical samples simultaneously for creating the feature-based surrogate model. The proposed technique is demonstrated using two microwave filter examples.