Araştırma Makalesi
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ÇOK AMAÇLI EVRİMSEL ALGORİTMALAR İLE FİLTRE TASARIMI

Yıl 2022, Cilt: 10 Sayı: 1, 201 - 216, 23.03.2022
https://doi.org/10.21923/jesd.935175

Öz

Birçok iletişim sistemi, radyo frekans (RF) filtreleriyle sinyal işleyen bir radyo frekans ön ucuna ihtiyaç duyar. Mikroşerit filtreler bunu gerçekleştirebilmenin oldukça düşük maliyetli ve kolay bir yöntemidir. Filtreler, mikrodalga teknolojisini kullanan uygulamalarda önemli bir yere sahiptir. Aynı zamanda mikroşerit filtreler, GSM (900MHz,1800MHz), WLAN (2,45GHz), WİMAX (3,5GHz) vb. kablosuz ve mobil haberleşme sistemlerindeki gelişmelerle beraber yoğun olarak kullanılmaktadır. Kullanılabilir boyut, yüksek performans ve düşük maliyet gibi ortaya atılan kriterleri karşılamak için milimetre ve mikrodalga sistemlere artan büyük bir ilgi vardır. Bu makalede, dizi (filtre kat sayısı) n = 8-12 arası değişen değerler için 1,6 mm dielektrik yüksekliğine sahip, geçirgenlik 4,4 değeri için WLAN (2,45GHz) ve WİMAX (3,5GHz) frekansında çalışan mikroşerit düzeni kullanılarak düşük maliyetli ve düşük ekleme kayıplı S-bant alçak geçiren filtrenin (AGF) tasarımını evrimsel algoritmalar ile kolaylaştırılmasını göstermektedir. Bu çalışmada standart yapılanlara ek olarak değişken filtre kat sayısı ve simetri durumu problemin zorluk derecesini bir basamak daha ileri götürmektedir. Tasarım simülasyonu, MATLAB programı kullanılarak gerçekleştirilmektedir. Tasarım sonucunda algoritmaların başarı grafiklerinin yanı sıra her algoritma için tasarlanan filtrenin S11 ve S21 (dB) parametreleri MATLAB programı ile çizdirilmiştir. En başarılı sonuç olan diferansiyel evrim algoritması ile yapılan optimizasyon ile elde edildiği görülmüş ve farklı bir frekans bandı için ayrıca bir yapılmıştır.

Kaynakça

  • Wells J., 2009. MM-Waves in the Living Room: The Future of Wireless High Definition Multimedia. Microwave Journal, 62(8), 72-84.
  • Güneş F., Demirel S., Mahouti P., 2014. Design of a Front–End Amplifier for the Maximum Power Delivery and Required Noise by HBMO with Support Vector Microstrip Model. Radioengineering, 23(1).
  • Güneş F., Demirel S., Mahouti P., 2015. A Simple and Efficient Honey Bee Mating Optimization Approach to Performance Characterization of a Microwave Transistor for the Maximum Power Delivery and Required Noise. Int. J. Numer. Model., doi: 10.1002/jnm.2041.
  • Storn R., Price K., 1997. Differential Evolution–A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journalof Global Optimization, Springer US, 341-359.
  • Yıldırım A., Mahouti P., Güneş F., 2016. Diferansiyel Evrim Algoritması Kullanılarak Mikrodalga Transistör Performans Analizi. Akıllı Sistemlerde Yenilikler ve Uygulamaları (ASYU) Sempozyumu, 29Eylül-1 Ekim 2016 Düzce, Türkiye
  • Yıldırım A., Güneş F., Belen M. A., 2017. Differential Evolution Optimization applied to the Performance Analysis Of a Microwave Transistor. Sigma J Eng & Nat Sci 8(2), 135-144.
  • Güneş F., Belen M. A., Mahouti P., 2017. Competitive Evolutionary Algorithms for Building Performance Database of a Microwave Transistor. Int. J. Circuit Theory Appl., 46(2), 244_258, doi: 10.1002/cta.2386.
  • Pozar D.M., 2000. Microwave Engineering. John Wiley. JiaShen Hong G., Lancaster M.J., 2001. Microstrip Filters for RF/ Microwave Applications. John Wiley &Sons Inc.
  • Belen, M. A., Alıcı, M., Çor, A., Güneş, F., 2014. Performance Characterization of a Microwave Transistor Using Firefly Algorithm. Symposium of electrical- electronics and computer engineering ELECO, 27(29), 491-493.
  • Yang, X.S., 2009. Firefly Algorithms for Multimodal Optimization. Stochastic Algorithms: Foundations and applications, SAGA, Lecture notes in computer sciences, 5792, 169–178.
  • Yang, X. S., Deb, S., 2010. Engineering Optimization by Cuckoo Search. Int. J. Mathematical modelling and numerical optimization, 1(4), 330–343.
  • Wang, F., He, X. S., Wang, Y., Yang, S., 2012. Markov model and convergence analysis based on cuckoo search algorithm. Jisuanji Gongcheng/ Computer Engineering, 38(11), 180–185.
  • Yang, X. S, Deb, S., 2009. Cuckoo Search via Levy Flights. Proc. of world congress on nature & biologically inspired computing, 210–214.
  • Güneş, F., Karataev, T., Demirel, S., 2016. Composite right/left-handed transmission lines in use for ultrawideband matching of front-end amplifiers with modified cuckoo search optimization. International Journal of Numerical Modelling: Electronic networks, devices and Fields, DOI: 10.1002/jnm.21441.
  • Storn, R., Price, K., 1997. Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces. Journal of global optimization, 11(4), 341–359.
  • Das, S., Abraham, A. Chacraborty, U.K., Konar, A., 2009. Differential evolution using a neighborhood-based mutation operator. IEEE Transactions on evolutionary computation, 13(3), 526–553.
  • Das, S., Suganthan, P.N., 2011. Differential Evolution: A Survey of the State-of-the-Art. IEEE Transactions on Evolutionary Computation, 15(1), 4-31.
  • Yang, X-S., (2013). Multiobjective Firefly Algorithm for Continuous Optimization, Engineering with Computers. Engineering with Computers, 29(2), 175-184.

FILTER DESIGN WITH MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS

Yıl 2022, Cilt: 10 Sayı: 1, 201 - 216, 23.03.2022
https://doi.org/10.21923/jesd.935175

Öz

Many communication systems require a radio frequency front end that processes signals with radio frequency (RF) filters. Microstrip filters are a very low cost and easy way to do this. Filters have an important place in applications using microwave technology. Also, microstrip filters, GSM (900MHz, 1800MHz), WLAN (2.45GHz), WIMAX (3.5GHz) etc. It is used extensively with the developments in wireless and mobile communication systems. There is a growing interest in millimeter and microwave systems to meet the criteria put forward such as usable size, high performance and low cost. In this article, the array (filter coefficient) has a dielectric height of 1.6 mm for values ranging from n = 8-12, using a microstrip scheme operating at WLAN (2.45GHz) and WIMAX (3.5GHz) frequencies for a transmittance value of 4.4. It shows that the design of a low cost and low insertion loss S-band low-pass filter (LPF) is facilitated by evolutionary algorithms. In this study, in addition to the standard ones, the variable filter coefficient and symmetry situation take the difficulty level of the problem one step further. Design simulation is carried out using the MATLAB program. As a result of the design, the S11 and S21 (dB) parameters of the filter designed for each algorithm, as well as the success graphs of the algorithms, were drawn with the MATLAB program. It was seen that the most successful result was obtained with the optimization made with the differential evolution algorithm and another one was made for a different frequency band.

Kaynakça

  • Wells J., 2009. MM-Waves in the Living Room: The Future of Wireless High Definition Multimedia. Microwave Journal, 62(8), 72-84.
  • Güneş F., Demirel S., Mahouti P., 2014. Design of a Front–End Amplifier for the Maximum Power Delivery and Required Noise by HBMO with Support Vector Microstrip Model. Radioengineering, 23(1).
  • Güneş F., Demirel S., Mahouti P., 2015. A Simple and Efficient Honey Bee Mating Optimization Approach to Performance Characterization of a Microwave Transistor for the Maximum Power Delivery and Required Noise. Int. J. Numer. Model., doi: 10.1002/jnm.2041.
  • Storn R., Price K., 1997. Differential Evolution–A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journalof Global Optimization, Springer US, 341-359.
  • Yıldırım A., Mahouti P., Güneş F., 2016. Diferansiyel Evrim Algoritması Kullanılarak Mikrodalga Transistör Performans Analizi. Akıllı Sistemlerde Yenilikler ve Uygulamaları (ASYU) Sempozyumu, 29Eylül-1 Ekim 2016 Düzce, Türkiye
  • Yıldırım A., Güneş F., Belen M. A., 2017. Differential Evolution Optimization applied to the Performance Analysis Of a Microwave Transistor. Sigma J Eng & Nat Sci 8(2), 135-144.
  • Güneş F., Belen M. A., Mahouti P., 2017. Competitive Evolutionary Algorithms for Building Performance Database of a Microwave Transistor. Int. J. Circuit Theory Appl., 46(2), 244_258, doi: 10.1002/cta.2386.
  • Pozar D.M., 2000. Microwave Engineering. John Wiley. JiaShen Hong G., Lancaster M.J., 2001. Microstrip Filters for RF/ Microwave Applications. John Wiley &Sons Inc.
  • Belen, M. A., Alıcı, M., Çor, A., Güneş, F., 2014. Performance Characterization of a Microwave Transistor Using Firefly Algorithm. Symposium of electrical- electronics and computer engineering ELECO, 27(29), 491-493.
  • Yang, X.S., 2009. Firefly Algorithms for Multimodal Optimization. Stochastic Algorithms: Foundations and applications, SAGA, Lecture notes in computer sciences, 5792, 169–178.
  • Yang, X. S., Deb, S., 2010. Engineering Optimization by Cuckoo Search. Int. J. Mathematical modelling and numerical optimization, 1(4), 330–343.
  • Wang, F., He, X. S., Wang, Y., Yang, S., 2012. Markov model and convergence analysis based on cuckoo search algorithm. Jisuanji Gongcheng/ Computer Engineering, 38(11), 180–185.
  • Yang, X. S, Deb, S., 2009. Cuckoo Search via Levy Flights. Proc. of world congress on nature & biologically inspired computing, 210–214.
  • Güneş, F., Karataev, T., Demirel, S., 2016. Composite right/left-handed transmission lines in use for ultrawideband matching of front-end amplifiers with modified cuckoo search optimization. International Journal of Numerical Modelling: Electronic networks, devices and Fields, DOI: 10.1002/jnm.21441.
  • Storn, R., Price, K., 1997. Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces. Journal of global optimization, 11(4), 341–359.
  • Das, S., Abraham, A. Chacraborty, U.K., Konar, A., 2009. Differential evolution using a neighborhood-based mutation operator. IEEE Transactions on evolutionary computation, 13(3), 526–553.
  • Das, S., Suganthan, P.N., 2011. Differential Evolution: A Survey of the State-of-the-Art. IEEE Transactions on Evolutionary Computation, 15(1), 4-31.
  • Yang, X-S., (2013). Multiobjective Firefly Algorithm for Continuous Optimization, Engineering with Computers. Engineering with Computers, 29(2), 175-184.
Toplam 18 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Elektrik Mühendisliği
Bölüm Araştırma Makaleleri \ Research Articles
Yazarlar

Ahmet Uluslu 0000-0002-5580-1687

Yayımlanma Tarihi 23 Mart 2022
Gönderilme Tarihi 9 Mayıs 2021
Kabul Tarihi 1 Ekim 2021
Yayımlandığı Sayı Yıl 2022 Cilt: 10 Sayı: 1

Kaynak Göster

APA Uluslu, A. (2022). ÇOK AMAÇLI EVRİMSEL ALGORİTMALAR İLE FİLTRE TASARIMI. Mühendislik Bilimleri Ve Tasarım Dergisi, 10(1), 201-216. https://doi.org/10.21923/jesd.935175