A Hybrid Neuro-Fuzzy Controller for Brushless DC Motors

A Hybrid Neuro-Fuzzy Controller for Brushless DC Motors

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...

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Hauptverfasser: Gökbulut, Muammer, Dandil, Beşir, Bal, Cafer
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Sprache:eng
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Applied sciences
Artificial intelligence
BLDC Motor
Computer science
control theory
systems
Direct Torque Control
Exact sciences and technology
Fuzzy Neural Network
Propose Control System
Steady State Error
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Dandil, Beşir
Bal, Cafer
description 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.
doi_str_mv 10.1007/11803089_15
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source Springer Books
subjects Applied sciences
Artificial intelligence
BLDC Motor
Computer science
control theory
systems
Direct Torque Control
Exact sciences and technology
Fuzzy Neural Network
Propose Control System
Steady State Error
title A Hybrid Neuro-Fuzzy Controller for Brushless DC Motors
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