Review of ANFIS-based control of induction motors

Article type: Research Article

Authors: Masood, M.K. | Hew, Wooi Ping | Rahim, Nasrudin Abd.

Affiliations: Department of Electrical Engineering, University of Malaya, Kuala Lumpur, Malaysia

Note: [] Corresponding author. M.K. Masood, Department of Electrical Engineering, University of Malaya, Kuala Lumpur, Malaysia. Tel.: +60 193764751; E-mail: mkm_imn@hotmail.com

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.

Keywords: ANFIS, induction motor, flux, parameter, torque

DOI: 10.3233/IFS-2012-0502

Journal: Journal of Intelligent & Fuzzy Systems, vol. 23, no. 4, pp. 143-158, 2012