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International Joint Conference CISIS’12-ICEUTE´12-SOCO´12 Special Sessions pp 429–438Cite as

Genetic Algorithm Based Optimization of MGP-FIR Current Reference Generator for Active Power Filters

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 189))

Abstract

This paper describes genetic algorithm (GA) based optimization of multiplicative general parameter finite impulse response filter (MGP-FIR) current reference signal generator for shunt-type active power filters. The MGP-FIR consists of two fixed subfilters with GA’s preoptimized fixed-point coefficients sharing one common delay line and two general adaptive multiplicative parameters to avoid harmful phase shift during fundamental frequency fluctuations. Presented theoretical conclusions are verified by simulation results and experiments performed on a designed laboratory prototype of the single-phase active power filter.

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References

  1. El-Habrouk, M., Darwish, M.K., Mehta, P.: Active power filters: A review. IEE Proc.-Electric Power Applications 147, 493–413 (2000)

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  2. Ovaska, S.J., Vainio, O.: Evolutionary-programming-based optimization of reduced-rank adaptive filters for reference generation in active power filters. IEEE Transactions on Industrial Electronics 51(4), 910–916 (2002)

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  3. Komrska, T., Žák, J., Ovaska, S., Peroutka, Z.: Computationally Efficient Current Reference Generator for 50-Hz and 16.7-Hz Shunt Active Power Filters. International Journal of Electronics 97(1), 63–81 (2010)

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  4. Martikainen, J., Ovaska, S.J.: Designing multiplicative general parameter filters using multipopulation genetic algorithm. In: Proceedings of the 6th Nordic Signal Processing Symposium, NORSIG 2004, pp. 25–28 (2004)

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Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering, Regional Innovation Center for Electrical Engineering (RICE), University of West Bohemia, Pilsen, Czech Republic

    Jakub Talla & Zdenek Peroutka

  2. Department of Electrical Engineering, Aalto University, Aalto, Finland

    Seppo J. Ovaska

  3. Faculty of Electrical Engineering, Department of Applied Electronics, University of West Bohemia, Pilsen, Czech Republic

    Josef Stehlik

Authors
  1. Jakub Talla
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  2. Zdenek Peroutka
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  3. Seppo J. Ovaska
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  4. Josef Stehlik
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Corresponding author

Correspondence to Jakub Talla .

Editor information

Editors and Affiliations

  1. , Department of Civil Engineering, University of Burgos, Campus Vena (Edif.C), C/ Francisco de Vitoria, s/n, Burgos, 09006, Spain

    Álvaro Herrero

  2. VŠB-TU Ostrava, 17. listopadu 15, Ostrava, 70833, Czech Republic

    Václav Snášel

  3. MIR Labs, Scientific Network for Innovation, Machine Intelligence Research Labs, Auburn, 98071, USA

    Ajith Abraham

  4. VŠB-TU Ostrava, 17. listopadu 15, Ostrava, 70833, Czech Republic

    Ivan Zelinka

  5. , Department of Civil Engineering, University of Burgos, Campus Vena (Edif.C), C/ Francisco de Vitoria, s/n, Burgos, 09006, Spain

    Bruno Baruque

  6. Universidad de Salamanca, Plaza de la Merced S/N, Salamanca, 37008, Spain

    Héctor Quintián

  7. University of Coruña, Avda. 19 de febrero, s/n, Coruña, 15405 A, Spain

    José Luis Calvo

  8. y León, Pol. Ind. Villalonquéjar, Instituto Tecnológico de Castilla, Lopez Bravo 70, Burgos, 09001, Spain

    Javier Sedano

  9. Universidad de Salamanca, Plaza de la Merced S/N, Salamanca, 37008, Spain

    Emilio Corchado

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© 2013 Springer-Verlag Berlin Heidelberg

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Cite this paper

Talla, J., Peroutka, Z., Ovaska, S.J., Stehlik, J. (2013). Genetic Algorithm Based Optimization of MGP-FIR Current Reference Generator for Active Power Filters. In: Herrero, Á., et al. International Joint Conference CISIS’12-ICEUTE´12-SOCO´12 Special Sessions. Advances in Intelligent Systems and Computing, vol 189. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33018-6_44

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  • DOI: https://doi.org/10.1007/978-3-642-33018-6_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33017-9

  • Online ISBN: 978-3-642-33018-6

  • eBook Packages: EngineeringEngineering (R0)

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