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A Hybrid Neuro-Fuzzy Controller for Brushless DC Motors

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Artificial Intelligence and Neural Networks (TAINN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3949))

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Abstract

In this paper, a hybrid neuro-fuzzy controller (NFC) is presented for the speed control of brushless DC motors to improve the control performance of the drive under transient and steady state conditions. In the hybrid control system, proportional-derivative (PD) type neuro-fuzzy controller (NFC) is the main tracking controller, and an integral compensator is proposed to compensate the steady state errors. A simple and smooth activation mechanism described for integral compensator modifies the control law adaptively. The presented BLDC drive has fast tracking capability, less steady state error and robust to load disturbance, and do not need complicated control method. Experimental results showing the effectiveness of the proposed control system are presented.

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Authors and Affiliations

  1. Faculty of Technical Edu., Dep. of Electr. and Computer Science Elazig, Firat U., Turkey

    Muammer Gökbulut, Beşir Dandil & Cafer Bal

Authors
  1. Muammer Gökbulut
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  2. Beşir Dandil
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  3. Cafer Bal
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Editor information

Editors and Affiliations

  1. Izmir Institute of Technology, Electrical Electronics Engineering, Gülbahçe, Urla, Izmir, Turkey

    F. Acar Savacı

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© 2006 Springer-Verlag Berlin Heidelberg

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Gökbulut, M., Dandil, B., Bal, C. (2006). A Hybrid Neuro-Fuzzy Controller for Brushless DC Motors. In: Savacı, F.A. (eds) Artificial Intelligence and Neural Networks. TAINN 2005. Lecture Notes in Computer Science(), vol 3949. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11803089_15

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  • DOI: https://doi.org/10.1007/11803089_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-36713-0

  • Online ISBN: 978-3-540-36861-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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