Adaptive space mapping with convergence enhancement for optimization of microwave structures and devices

A novel space mapping algorithm is presented that adaptively adjusts the type of space mapping surrogate model used in a given iteration, based on the approximation and generalization capabilities of the model, its ability to satisfy the design specifications, as well as convergence properties of the iterative optimization process. The new technique allows us to avoid a wrong choice of space mapping surrogate which might lead to poor performance of the space mapping algorithm. No extra fine model evaluations are necessary as the assessment process uses only data emerging naturally during the optimization procedure. The performance of the method is verified using microwave design optimization examples and is compared with the previously published adaptive space mapping algorithm.