The Design of Bessel Type High-Pass Active Filter with Charged System Search Algorithm

Abstract

Filtering is an important process used in many electronic circuit applications such as signal processing, communication and control. Electronic filter circuits that are used for filtering can be designed for many different purposes such as limiting band, passing band or stopping band for a specific frequency area. In this study, of a 10th degree Sallen-Key structure design of a Bessel Type high-pass active filter whose debilitation is much more than the other filter types in the passing band. The optimum values of the designed filter’s circuit elements have been defined for the continuous case by using charged system search algorithm (CSS). The total error has been minimized by accepting the component values as unlimited for the continuous case. The obtained optimum values together with the quality factors (Q) have been presented for each layer separately and the results have been discussed.

Keywords

• Active filters,high-pass filter,Bessel Type,10th degree filter design,Charged system search algorithm

The Design of Bessel Type High-Pass Active Filter with Charged System Search Algorithm

Abstract

Filtering is an important process used in many electronic circuit applications such as signal processing, communication and control. Electronic filter circuits that are used for filtering can be designed for many different purposes such as limiting band, passing band or stopping band for a specific frequency area. In this study, of a 10th degree Sallen-Key structure design of a Bessel Type high-pass active filter whose debilitation is much more than the other filter types in the passing band. The optimum values of the designed filter’s circuit elements have been defined for the continuous case by using charged system search algorithm (CSS). The total error has been minimized by accepting the component values as unlimited for the continuous case. The obtained optimum values together with the quality factors (Q) have been presented for each layer separately and the results have been discussed.

Keywords

• Active filters,high-pass filter,Bessel Type,10th degree filter design,Charged system search algorithm

References

1. [1] B. Durmuş, B. Hiçdurmaz, H. Temurtaş, S. Özyön, “Defining the Parameters of the High Pass Active Filter by Using Backtracking Search Algorithm” Proceedings of 2nd International Conference on Engineering and Natural Sciences 9 (2016) 2429-2435.
2. [2] R.P. Sallen, E.L. Key, “A practical method of designing RC active filters” IRE Transactions on Circuit Theory 2(1) (1955) 74-85.
3. [3] https://tr.qwertyu.wiki/wiki/Bessel_filter
4. [4] R. Mancini, “Op Amps for Everyone - Design References” Texas Instruments 2002.
5. [5] 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.
6. [6] 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.
7. [7] A.F. Sheta, “Analogue filter design using differential evolution,” International Journal of Bio-Inspired Computation 2(3) (2010) 233-241.
8. [8] 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.

9. [9] 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.
10. [10] 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.
11. [11] A. Kalinli, “Component value selection for active filters using parallel tabu search algorithm” AEÜ - International Journal of Electronics and Communications 60 (2006) 85-92.
12. [12] 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.
13. [13] 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.
14. [14] S. Gholami-Boroujeny, M. Eshghi, “Non-linear active noise cancellation using a bacterial foraging optimisation algorithm” IET Signal Processing 6 (2012) 364-373.
15. [15] 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.
16. [16] 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.
17. [17] A. Kaveh, S. Talahatari, “A novel heuristic optimization method: charged system search” Acta Mechanica 213(3-4) 2010 267-289.
18. [18] A. Kaveh, M. Khanzadi, M.R. Moghaddam, M. Rezazadeh, “Charged system search and magnetic charged system search algorithms for construction site layout planning optimization” Periodica Polytechnica Civil Engineering 62(4) 2018 841-850.
19. [19] J. Karki, “Active low-pass filter design” Texas Instruments, Dallas-Texas, Application Rep. SLOA049B, 2002.