Imperfect manufacturing is one of the factors affecting the performance of antenna systems. It is particularly important when design specifications are strict and leave a minimum leeway for a degradation caused by geometry or material parameter deviations from their nominal values. At the same time, conventional antenna design procedures routinely neglect to take the fabrication tolerances into account, which is mainly a result of a challenging nature of uncertainty quantification. Nevertheless, the ability to assess the effects of parameter deviations and to mitigate thereof is instrumental in achieving truly robust antenna designs. Furthermore, identifying the antenna-specific relationships be-tween nominal requirements and tolerance immunity is essential to determine the necessary levels of fabrication accuracy, which affects both the reliability and the manufacturing costs. This paper proposes a technique for multi-criterial optimization of antenna structures oriented towards rendering a family of designs rep-resenting trade-offs between the nominal performance and the robustness. The fundamental components of our procedure are feature-based regression models constructed at the level of selected characteristic points of the antenna outputs. The trade-off designs are generated sequentially, using local search carried out for gradually relaxed nominal requirements. Numerical experiments conducted for two microstrip antennas demonstrate that the proposed algorithm is capable of yielding the performance/robustness Pareto set at the cost of only a few dozens of EM analysis of the antenna at hand per design, while ensuring reliability, as validated by means of EM-based Monte Carlo simulation.
Authors
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1007/978-3-031-08757-8_19
- Category
- Aktywność konferencyjna
- Type
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Language
- angielski
- Publication year
- 2022
