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Titolo:
Direct self control of induction motor based on neural network
Autore:
Shi, KT; Chan, TF; Wong, YK; Ho, SL;
Indirizzi:
Honeywell Aerosp Canada, Honeywell Engn & Syst, Mississauga, ON L5L 3C6, Canada Honeywell Aerosp Canada Mississauga ON Canada L5L 3C6 ON L5L 3C6, Canada Hong Kong Polytech Univ, Dept Elect Engn, Kowloon, Hong Kong, Peoples R China Hong Kong Polytech Univ Kowloon Hong Kong Peoples R China eoples R China Hong Kong Polytech Univ, Dept Elect Engn, Kowloon, Hong Kong, Peoples R China Hong Kong Polytech Univ Kowloon Hong Kong Peoples R China eoples R China
Titolo Testata:
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
fascicolo: 5, volume: 37, anno: 2001,
pagine: 1290 - 1298
SICI:
0093-9994(200109/10)37:5<1290:DSCOIM>2.0.ZU;2-F
Fonte:
ISI
Lingua:
ENG
Keywords:
direct self control; induction motor drive; Matlab/Simulink; neural networks;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
11
Recensione:
Indirizzi per estratti:
Indirizzo: Shi, KT Ryerson Polytech Inst, Dept Elect & Comp Engn, Toronto, ON M5B 2K3, Canada Ryerson Polytech Inst Toronto ON Canada M5B 2K3 N M5B 2K3, Canada
Citazione:
K.T. Shi et al., "Direct self control of induction motor based on neural network", IEEE IND AP, 37(5), 2001, pp. 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 orderto 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.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 21/09/20 alle ore 06:02:06