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Speed control of a brushless DC motor drive via adaptive neuro-fuzzy controller based on emotional learning algorithm

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3 Author(s)
Niasar, A.H. ; Dept. of Electr. Eng., Iran Univ. of Sci. & Technol., Tehran, Iran ; Vahedi, A. ; Moghbelli, H.

Principle of a new adaptive neuro-fuzzy controller (NFC) is introduced and is used speed control of brushless DC (BLDC) motor drives. The proposed algorithm has advantages of neural and fuzzy networks and uses a supervised emotional learning process to train the NFC. This newly developed design leads to a controller with minimum hardware and improved dynamic performance. System implementation is relatively easy since it requires less calculation as compared with the conventional fuzzy and/or neural networks, used for electrical drive applications. The proposed controller is used for speed and/or torque control of a BLDC motor drive. In order to demonstrate the NFC ability to follow the reference speed and to reject undesired disturbances, its performance is simulated and compared with that of a conventional PID controller.

Published in:

Electrical Machines and Systems, 2005. ICEMS 2005. Proceedings of the Eighth International Conference on  (Volume:1 )

Date of Conference:

27-29 Sept. 2005

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