A trust region aggressive space mapping algorithm for EM optimization

A robust new algorithm for electromagnetic (EM) optimization of microwave circuits is presented. The algorithm (TRASM) integrates a trust region methodology with the aggressive space mapping (ASM). The trust region ensures that each iteration results in improved alignment between the coarse and fine...

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Bibliographic Details
Published in:IEEE transactions on microwave theory and techniques 1998-12, Vol.46 (12), p.2412-2425
Main Authors: Bakr, M.H., Bandler, J.W., Biernacki, R.M., Shao Hua Chen, Madsen, K.
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Circuit simulation
Electromagnetic waveguides
High temperature superconductors
Microwave circuits
Microwave filters
Parameter extraction
Robustness
Superconducting filters
Transformers
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Summary:A robust new algorithm for electromagnetic (EM) optimization of microwave circuits is presented. The algorithm (TRASM) integrates a trust region methodology with the aggressive space mapping (ASM). The trust region ensures that each iteration results in improved alignment between the coarse and fine models needed to execute ASM. The parameter extraction step is a crucial part of the ASM technique. The nonuniqueness of this step may result in the divergence of the technique. To improve the uniqueness of the extraction phase, we developed a recursive multipoint parameter extraction. This suggested step exploits all the available EM simulations for improving the uniqueness of parameter extraction. The new algorithm was successfully used to design a number of microwave circuits. Examples include the EM optimization of a double-folded stub filter and of a high-temperature superconducting (HTS) filter using Sonnet's em. The proposed algorithm was also used to design two-section, three-section, and seven-section waveguide transformers exploiting Maxwell Eminence. The design of a three-section waveguide transformer with rounded corners was carried out using HP HFSS. We show how the mapping can be used to carry out Monte Carlo analysis using only coarse model simulations.
ISSN:0018-9480
1557-9670
DOI:10.1109/22.739229