Slot Parameter Optimization for Multiband Antenna Performance Improvement Using Intelligent Systems
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Dosyalar
Tarih
2015
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Hindawi Publishing Corporation
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This paper discusses bandwidth enhancement for multiband microstrip patch antennas (MMPAs) using symmetrical rectangular/square slots etched on the patch and the substrate properties. The slot parameters on MMPA are modeled using soft computing technique of artificial neural networks (ANN). To achieve the best ANN performance, Particle Swarm Optimization (PSO) and Differential Evolution (DE) are applied with ANN's conventional training algorithm in optimization of the modeling performance. In this study, the slot parameters are assumed as slot distance to the radiating patch edge, slot width, and length. Bandwidth enhancement is applied to a formerly designed MMPA fed by a microstrip transmission line attached to the center pin of 50 ohm SMA connecter. The simulated antennas are fabricated and measured. Measurement results are utilized for training the artificial intelligence models. The ANN provides 98% model accuracy for rectangular slots and 97% for square slots; however, ANFIS offer 90% accuracy with lack of resonance frequency tracking. © 2015 Erdem Demircioglu et al.
Açıklama
Anahtar Kelimeler
Kaynak
International Journal of Antennas and Propagation
WoS Q Değeri
Q3
Scopus Q Değeri
Q3
Cilt
2015
