Repozytorium publikacji - Politechnika Gdańska

A surrogate-based technique for efficient multi-objective antenna optimization is discussed. Our approach exploits response surface approximation (RSA) model constructed from low-fidelity antenna model data (here, obtained through coarse-discretization electromagnetic simulations). The RSA model enables fast determination of the best available trade-offs between conflicting design goals. The cost of RSA model construction for multi-parameter antennas is significantly lowered through initial design space reduction. Optimization of the response surface approximation model is carried out by a multi-objective evolutionary algorithm. Additional response correction techniques are subsequently applied to improve selected designs at the level of high-fidelity electromagnetic antenna model. The refined designs constitute the final Pareto set representation. The pre-sented multi-objective design approach is validated using three examples: a six-variable ultra-wideband dipole antenna, an eight-variable planar Yagi-Uda anten-na and an ultra-wideband monocone with thirteen design variables.

Autorzy

• dr hab. inż. Adrian Bekasiewicz link otwiera się w nowej karcie ,
• prof. dr inż. Sławomir Kozieł link otwiera się w nowej karcie ,
• prof. dr hab. inż. Włodzimierz Zieniutycz link otwiera się w nowej karcie