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The Estimation of Bessel Type Low-Pass Active Filter Parameters with Charged System Search Algorithm

Year 2019, Volume: 3 Issue: 2, 67 - 75, 31.12.2019

Abstract

Filter circuits are one of the significant elements of communication systems. These circuits are ones that provide the characteristic of decay at a demanded level or a delay at a demanded time in a defined frequency area. They are also accepted as selective devices that pass or block the values under or over a defined frequency and can be designed for many different purposes. In this study the design of a 10th degree Sallen-Key structure Bessel type low pass filter (SK-B-AGF) whose component selections and gain calculations take a long time with traditional methods, has been done.  And what the component values of the designed filter will be, has been optimized for continious values by using charged system search algorithm (CSS). In the case where constant values have been used, the total error has been minimized by accepting the component values as ideal and unlimited. The obtained optimum filter component values together with have been presented for each stage the quality factor (Q), the results have been evaluated.

References

  • [1] R.P. Sallen, E.L. Key, “A practical method of designing RC active filters” IRE Transactions on Circuit Theory 2(1) (1955) 74-85.
  • [2] B. Hiçdurmaz, B. Durmuş, H. Temurtaş, S. Özyön, “The prediction of butterworth type active filter parameters in low pass sallen key topology by backtracking search algorithm” Proceedings of 2nd International Conference on Engineering and Natural Sciences 9 (2016) 2422-2428.
  • [3] B. Durmuş, H. Temurtaş, S. Özyön, “Optimizasyon algoritmalarının ile çoklu geri-beslemeli yüksek geçiren aktif filtre tasarımı” Mühendislik Alanında Araştırma ve Değerlendirmeler, Editör: Dr. Mahmut TURAN, p.123-147, Gece Akademi, 2019, Ankara. ISBN: 978-605-7852-96-0.
  • [4] R.A. Vural, T. Yıldırım, T. Kadioğlu, A. Basargan, “Performance evaluation of evolutionary algorithms for optimal filter design” IEEE Transactions on Evolutionary Computation 16 (2012) 135-147.
  • [5] D. Ustun, M. Akkus, M.B. Bicer, H. Temurtas, A. Akdagli, “Sezgisel algoritmalar ile Butterworth ve Chebyshev alçak geçiren filre tasarımı” Sinyal İşleme ve İletişim Uygulamaları Kurultayı (SIU-2015) (2015) 108-111.
  • [6] B.P. De, R. Kar, D. Mandal, S.P. Ghoshal, “Optimal selection of components value for analog active filter design using simplex particle swarm optimization” International Journal of Machine Learning and Cybernetics 6(4) (2015) 621-636.
  • [7] B. Nayak, T.R. Choudhury, B. Misra, “Component value selection for active filters based on minimization of GSP and E12 compatible using Grey Wolf and Particle Swarm Optimization” AEÜ - International Journal of Electronics and Communications 87 (2018) 48-53.
  • [8] G.G. Bulut, H. Güler, M.T. Özdemir, “Optimal selection of components in a sixthorder Butterworth low-pass filter with using grey wolf algorithm” International Journal of Electrical, Electronics and Data Communication 5(10) (2017) 1-4.
  • [9] R.A. Vural, U. Bozkurt, T. Yildirim, “Analog active filter component selection with nature inspired metaheuristics” AEÜ - International Journal of Electronics and Communications 67(3) (2013) 197-205.
  • [10] A.F. Sheta, “Analogue filter design using differential evolution,” International Journal of Bio-Inspired Computation 2(3) (2010) 233-241.
  • [11] M. Jiang, Z. Yang, Z. Gan, “Optimal components selection for analog active filters using clonal selection algorithm” Proceedings of International Conference on Intelligent Computing (2007) 950-959.
  • [12] A. Kalinli, “Component value selection for active filters using parallel tabu search algorithm” AEÜ - International Journal of Electronics and Communications 60 (2006) 85-92.
  • [13] T. Kaya, H. Guler, “A hybrid genetic algorithm for analog active filter component selection” AEÜ - International Journal of Electronics and Communications 86 (2018) 1-7.
  • [14] D.H. Horrocks, M.C. Spittle, “Component value selection for active filters using genetic algorithms” Proceedings IEEE Workshop on Natural Algorithms in Signal Processing 1(13) (1993) 1-6.
  • [15] B. Doğan, T. Ölmez, “Vortex search algorithm for the analog active filter component selection problem” AEÜ - International Journal of Electronics and Communications 69(9) (2015) 1243-1253.
  • [16] S. Gholami-Boroujeny, M. Eshghi, “Non-linear active noise cancellation using a bacterial foraging optimisation algorithm” IET Signal Processing 6 (2012) 364-373.
  • [17] D. Bose, S. Biswas, A.V. Vasilakos, S. Laha, “Optimal filter design using an improved artificial bee colony algorithm” Information Sciences 281 (2014) 443-461.
  • [18] A. Kaveh, S. Talahatari, “A novel heuristic optimization method: charged system search” Acta Mechanica 213(3-4) 2010 267-289.
  • [19] R. Sheikholeslami, A. Kaveh, A. Tahershamsi, S. Talatahari, “Application of charged system search algorithm to water distrubition networks optimization” International Journal of Optimization in Civil Engineering 4(1) 2014 41-58.
  • [20] R. Mancini, “Op Amps for Everyone - Design References” Texas Instruments 2002.

The Estimation of Bessel Type Low-Pass Active Filter Parameters with Charged System Search Algorithm

Year 2019, Volume: 3 Issue: 2, 67 - 75, 31.12.2019

Abstract

Filter circuits are one of the significant elements of
communication systems. These circuits are ones that provide the characteristic
of decay at a demanded level or a delay at a demanded time in a defined
frequency area. They are also accepted as selective devices that pass or block
the values under or over a defined frequency and can be designed for many
different purposes. In this study the design of a 10th degree Sallen-Key
structure Bessel type low pass filter (SK-B-AGF) whose component selections and
gain calculations take a long time with traditional methods, has been
done.  And what the component values of
the designed filter will be, has been optimized for continious values by using
charged system search algorithm (CSS). In the case where constant values have
been used, the total error has been minimized by accepting the component values
as ideal and unlimited. The obtained optimum filter component values together
with have been presented for each stage the quality factor (Q), the results
have been evaluated.

References

  • [1] R.P. Sallen, E.L. Key, “A practical method of designing RC active filters” IRE Transactions on Circuit Theory 2(1) (1955) 74-85.
  • [2] B. Hiçdurmaz, B. Durmuş, H. Temurtaş, S. Özyön, “The prediction of butterworth type active filter parameters in low pass sallen key topology by backtracking search algorithm” Proceedings of 2nd International Conference on Engineering and Natural Sciences 9 (2016) 2422-2428.
  • [3] B. Durmuş, H. Temurtaş, S. Özyön, “Optimizasyon algoritmalarının ile çoklu geri-beslemeli yüksek geçiren aktif filtre tasarımı” Mühendislik Alanında Araştırma ve Değerlendirmeler, Editör: Dr. Mahmut TURAN, p.123-147, Gece Akademi, 2019, Ankara. ISBN: 978-605-7852-96-0.
  • [4] R.A. Vural, T. Yıldırım, T. Kadioğlu, A. Basargan, “Performance evaluation of evolutionary algorithms for optimal filter design” IEEE Transactions on Evolutionary Computation 16 (2012) 135-147.
  • [5] D. Ustun, M. Akkus, M.B. Bicer, H. Temurtas, A. Akdagli, “Sezgisel algoritmalar ile Butterworth ve Chebyshev alçak geçiren filre tasarımı” Sinyal İşleme ve İletişim Uygulamaları Kurultayı (SIU-2015) (2015) 108-111.
  • [6] B.P. De, R. Kar, D. Mandal, S.P. Ghoshal, “Optimal selection of components value for analog active filter design using simplex particle swarm optimization” International Journal of Machine Learning and Cybernetics 6(4) (2015) 621-636.
  • [7] B. Nayak, T.R. Choudhury, B. Misra, “Component value selection for active filters based on minimization of GSP and E12 compatible using Grey Wolf and Particle Swarm Optimization” AEÜ - International Journal of Electronics and Communications 87 (2018) 48-53.
  • [8] G.G. Bulut, H. Güler, M.T. Özdemir, “Optimal selection of components in a sixthorder Butterworth low-pass filter with using grey wolf algorithm” International Journal of Electrical, Electronics and Data Communication 5(10) (2017) 1-4.
  • [9] R.A. Vural, U. Bozkurt, T. Yildirim, “Analog active filter component selection with nature inspired metaheuristics” AEÜ - International Journal of Electronics and Communications 67(3) (2013) 197-205.
  • [10] A.F. Sheta, “Analogue filter design using differential evolution,” International Journal of Bio-Inspired Computation 2(3) (2010) 233-241.
  • [11] M. Jiang, Z. Yang, Z. Gan, “Optimal components selection for analog active filters using clonal selection algorithm” Proceedings of International Conference on Intelligent Computing (2007) 950-959.
  • [12] A. Kalinli, “Component value selection for active filters using parallel tabu search algorithm” AEÜ - International Journal of Electronics and Communications 60 (2006) 85-92.
  • [13] T. Kaya, H. Guler, “A hybrid genetic algorithm for analog active filter component selection” AEÜ - International Journal of Electronics and Communications 86 (2018) 1-7.
  • [14] D.H. Horrocks, M.C. Spittle, “Component value selection for active filters using genetic algorithms” Proceedings IEEE Workshop on Natural Algorithms in Signal Processing 1(13) (1993) 1-6.
  • [15] B. Doğan, T. Ölmez, “Vortex search algorithm for the analog active filter component selection problem” AEÜ - International Journal of Electronics and Communications 69(9) (2015) 1243-1253.
  • [16] S. Gholami-Boroujeny, M. Eshghi, “Non-linear active noise cancellation using a bacterial foraging optimisation algorithm” IET Signal Processing 6 (2012) 364-373.
  • [17] D. Bose, S. Biswas, A.V. Vasilakos, S. Laha, “Optimal filter design using an improved artificial bee colony algorithm” Information Sciences 281 (2014) 443-461.
  • [18] A. Kaveh, S. Talahatari, “A novel heuristic optimization method: charged system search” Acta Mechanica 213(3-4) 2010 267-289.
  • [19] R. Sheikholeslami, A. Kaveh, A. Tahershamsi, S. Talatahari, “Application of charged system search algorithm to water distrubition networks optimization” International Journal of Optimization in Civil Engineering 4(1) 2014 41-58.
  • [20] R. Mancini, “Op Amps for Everyone - Design References” Texas Instruments 2002.
There are 20 citations in total.

Details

Primary Language Turkish
Subjects Electrical Engineering
Journal Section Articles
Authors

Bahadır Hiçdurmaz 0000-0002-4610-1400

Fırat Ertaç Durak 0000-0002-4278-6561

Serdar Özyön 0000-0002-4469-3908

Publication Date December 31, 2019
Acceptance Date December 27, 2019
Published in Issue Year 2019 Volume: 3 Issue: 2

Cite

APA Hiçdurmaz, B., Durak, F. E., & Özyön, S. (2019). The Estimation of Bessel Type Low-Pass Active Filter Parameters with Charged System Search Algorithm. International Scientific and Vocational Studies Journal, 3(2), 67-75.
AMA Hiçdurmaz B, Durak FE, Özyön S. The Estimation of Bessel Type Low-Pass Active Filter Parameters with Charged System Search Algorithm. ISVOS. December 2019;3(2):67-75.
Chicago Hiçdurmaz, Bahadır, Fırat Ertaç Durak, and Serdar Özyön. “The Estimation of Bessel Type Low-Pass Active Filter Parameters With Charged System Search Algorithm”. International Scientific and Vocational Studies Journal 3, no. 2 (December 2019): 67-75.
EndNote Hiçdurmaz B, Durak FE, Özyön S (December 1, 2019) The Estimation of Bessel Type Low-Pass Active Filter Parameters with Charged System Search Algorithm. International Scientific and Vocational Studies Journal 3 2 67–75.
IEEE B. Hiçdurmaz, F. E. Durak, and S. Özyön, “The Estimation of Bessel Type Low-Pass Active Filter Parameters with Charged System Search Algorithm”, ISVOS, vol. 3, no. 2, pp. 67–75, 2019.
ISNAD Hiçdurmaz, Bahadır et al. “The Estimation of Bessel Type Low-Pass Active Filter Parameters With Charged System Search Algorithm”. International Scientific and Vocational Studies Journal 3/2 (December 2019), 67-75.
JAMA Hiçdurmaz B, Durak FE, Özyön S. The Estimation of Bessel Type Low-Pass Active Filter Parameters with Charged System Search Algorithm. ISVOS. 2019;3:67–75.
MLA Hiçdurmaz, Bahadır et al. “The Estimation of Bessel Type Low-Pass Active Filter Parameters With Charged System Search Algorithm”. International Scientific and Vocational Studies Journal, vol. 3, no. 2, 2019, pp. 67-75.
Vancouver Hiçdurmaz B, Durak FE, Özyön S. The Estimation of Bessel Type Low-Pass Active Filter Parameters with Charged System Search Algorithm. ISVOS. 2019;3(2):67-75.


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