Review of ANFIS-based control of induction motors

Authors:
M. K. Masood;Wooi Ping Hew;Nasrudin Abd. Rahim
Affiliations:
Department of Electrical Engineering, University of Malaya, Kuala Lumpur, Malaysia;Department of Electrical Engineering, University of Malaya, Kuala Lumpur, Malaysia;Department of Electrical Engineering, University of Malaya, Kuala Lumpur, Malaysia
Venue:
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Year:
2012

Citing 2
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IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

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Abstract

This paper reviews the use of Adaptive Neuro-Fuzzy Inference Systems ANFIS for vector-controlled induction motor drives. While conventional schemes do not deal well with the highly nonlinear nature of motor control, fuzzy logic with its adjustability and neural networks with their adaptability have been shown to be excellent alternatives. ANFIS combines the advantages of fuzzy logic and neural networks and yields excellent results when used at various stages of the motor control process. The most prominent use of ANFIS with motor drives has been for parameter estimation, speed control and torque and flux control. The merits and demerits of these methods are examined. This paper is intended to serve as a reference for researchers considering the use of ANFIS for the control of motor drives.