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A Hybrid Neuro-Fuzzy Controller for Brushless DC Motors

  • Muammer Gökbulut
  • Beşir Dandil
  • Cafer Bal
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3949)

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.

Keywords

Fuzzy Neural Network Steady State Error BLDC Motor Direct Torque Control Propose Control System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Muammer Gökbulut
    • 1
  • Beşir Dandil
    • 1
  • Cafer Bal
    • 1
  1. 1.Faculty of Technical Edu., Dep. of Electr. and Computer Science ElazigFirat U.Turkey

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