An Improved Genetic Algorithm for Optimizing EBG Structure With Ultra-Wideband SSN Suppression Performance of Mixed Signal Systems

In this paper, an improved genetic algorithm (GA) for automatically optimizing electromagnetic bandgap (EBG) structure with good power integrity performance is presented. The traditional GA is improved in several ways including Hamming Distance initialization, elite selection and non-repeating cross...

Full description

Saved in:
Bibliographic Details
Published in:IEEE access 2020, Vol.8, p.26129-26138
Main Authors: Zhu, Haoran, Wang, Jiabao, Sun, Yufa, Wu, Xian-Liang
Format: Article
Language:English
Subjects:
Automatic optimization
Convergence
Crossovers
Electric power distribution
electromagnetic band gap
Energy conversion efficiency
genetic algorithm
Genetic algorithms
Integrity
Metamaterials
multi objective optimization
Noise propagation
Optimization
Periodic structures
simultaneously switching noise
Sociology
Solution space
Statistics
Ultrawideband
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, an improved genetic algorithm (GA) for automatically optimizing electromagnetic bandgap (EBG) structure with good power integrity performance is presented. The traditional GA is improved in several ways including Hamming Distance initialization, elite selection and non-repeating crossover, which can generate initial population charactering solution space in detail, increase crossover efficiency, and accelerate convergence. Furthermore, an EBG structure for power distribution network is optimized with the presented GA method to improve the performances of power integrity. The simultaneous switching noise propagation can be prohibited from 0.38 GHz to 20 GHz with a suppression level of -60 dB. Good agreements between the measured results and the simulation ones are observed.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2971355