EM Optimization of Microwave Tunable Filter using Surrogate-Based Simultaneous Multiple Tuning-Driven Method

In this paper, a new technique is presented for optimizing microwave tunable filters. The technique, which is based on surrogate models, addresses the challenges of meeting multiple sets of tuning specifications simultaneously. By employing a collection of ideal solutions for fixed parameters and several sets of ideal solutions for adjustable parameters, the proposed technique achieves this goal. The surrogate model is made up of several sub-surrogate models, each with inputs of non-tunable and tunable parameters. The complete surrogate model has inputs of non-tunable parameters and multiple sets of tunable parameters. By optimizing all the design specifications together, the technique being suggested is more likely to discover appropriate solutions that meet all the requirements. Moreover, the method is more proficient in steering clear of local optima and achieving the optimal solution with greater efficiency compared to the current two-stage optimization approach used for distinct specifications. The validity of our technique is demonstrated using a tunable four-pole waveguide filter optimization.