Abstract

Geometry parameters of contemporary microwave passives have to be carefully tuned in the final stages of their design process to ensure the best possible performance. For reliability reasons, the tuning has to be carried out at the level of full-wave electromagnetic (EM) simulations. This is because traditional modeling methods are incapable of quantifying certain phenomena that may affect the operation and performance of these devices, such as cross-coupling effects. As a consequence, the designs yielded with the use of equivalent network models may only serve as starting points that need further refinement. Unfortunately, simulation-driven numerical optimization is computationally demanding even in the case of local search procedures. Thus, significant research efforts have been aimed toward identifying effective ways of expediting EM-driven optimization procedures, critical from the point of view of cost of design cycles. Among these, one may list the recently proposed multifidelity optimization frameworks. Another option for accelerating simulation-driven design procedures is sparse sensitivity updating schemes, where costly gradient estimation through finite differentiation (FD) is suppressed for selected variables. This work proposes a novel algorithm that capitalizes on both aforementioned mechanisms to reduce the optimization cost of local gradient-based parameter tuning of compact microwave components. In our approach, multifidelity optimization is further expedited by replacing expensive FD sensitivity updates with the Broyden formula for selected design variables. Verification using two microwave structures, a branch-line coupler and a power divider, demonstrates average savings of around 80% over the basic trust-region (TR) routine, with only minor degradation of the design quality.

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