Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/862
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Title: Direct self control of induction motor based on neural network
Authors: Shi, KL
Chan, TF
Wong, YK
Ho, SL 
Issue Date: Sep-2001
Source: IEEE transactions on industry applications, Sept./Oct. 2001, v. 37, no. 5, p. 1290-1298
Abstract: This paper presents an artificial-neural-network-based direct-self-control (ANN-DSC) scheme for an inverter-fed three-phase induction motor. In order to cope with the complex calculations required in direct self control (DSC), the proposed artificial-neural-network (ANN) system employs the individual training strategy with fixed-weight and supervised models. A computer simulation program is developed using Matlab/Simulink together with the Neural Network Toolbox. The simulated results obtained demonstrate the feasibility of ANN-DSC. Compared with the classical digital-signal-processor-based DSC, the proposed ANN-based scheme incurs much shorter execution times and, hence, the errors caused by control time delays are minimized.
Keywords: Direct self control
Induction motor drive
Matlab/Simulink
Neural networks
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE transactions on industry applications 
ISSN: 0093-9994
EISSN: 1939-9367
DOI: 10.1109/28.952504
Rights: © 2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
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