Adaptive network-based inference system models on multiband patch antenna design

Demircioglu E., SAZLI M. H., Sengul O., İMECİ Ş. T., ILGIN H. A.

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, cilt.23, sa.1, ss.118-125, 2015 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 23 Sayı: 1
  • Basım Tarihi: 2015
  • Doi Numarası: 10.3906/elk-1301-159
  • Dergi Adı: TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.118-125
  • Anahtar Kelimeler: Adaptive network-based fuzzy inference system, multiband microstrip patch antennas, EM simulator, modeling, RECTANGULAR MICROSTRIP ANTENNAS, RESONANT-FREQUENCY, COMPUTATION, THIN
  • Ankara Üniversitesi Adresli: Evet

Özet

In this study, an adaptive network-based fuzzy inference system (ANFIS) for multiband microstrip patch antenna (MMPA) modeling is proposed. The MMPA includes a single patch with inverted L-shaped stubs on the edges. The antenna production process needs iterative runs of the electromagnetic (EM) simulator, fabricating and testing the simulated antenna to find the optimum geometry. Production processes (design, simulation, fabrication, and testing) and the cost computation time add to the overall manufacturing expenses. A computer-aided modeling approach using the ANFIS is developed and trained with data acquired from the EM simulators, Sonnet Suites and AWR AXIEM, and measurement data. The overall data set includes 7777 input-output pairs, of which 3338 are used for the testing of the ANFIS model. The trained ANFIS model provides accurate and reliable results compared with the EM simulators and measured data.