Application of artificial neural network in the efficient control of three-phase induction motor

Author

Santos, A.F. ; Neves, F.A.S. ; Aquino, R.R.B. ; Cavalcanti, M.C.

Author_Institution

DEESP, Fed. Univ. of Pernambuco (UFPE), Recife, Brazil

fYear

2009

fDate

Sept. 27 2009-Oct. 1 2009

Firstpage

159

Lastpage

166

Abstract

This work presents a method for increasing the efficiency of three-phase induction motor drives over the entire operation range. The direct field oriented control of induction motors, including the effects of magnetic saturation is used. The magnetic saturation effect in the machine is modeled by the non-linear magnetization curve of the iron core. Artificial neural networks are used to predict the optimum reference rotor flux to be used in vector control. Details about the chosen neural networks are given. Simulation and experimental results are presented and the motor losses reduction during different load conditions is evaluated.

Keywords

induction motor drives; machine vector control; neurocontrollers; artificial neural network; direct field oriented control; iron core; magnetic saturation; nonlinear magnetization curve; three-phase induction motor control; three-phase induction motor drives; vector control; Artificial neural networks; Core loss; Induction machines; Induction motor drives; Induction motors; Magnetic flux; Rotors; Saturation magnetization; Tellurium; Torque; Artificial Neural Network; Energy Conservation; Induction Motor Drives;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Electronics Conference, 2009. COBEP '09. Brazilian

Conference_Location

Bonito-Mato Grosso do Sul

ISSN

2175-8603

Print_ISBN

978-1-4244-3369-8

Type

conf

DOI

10.1109/COBEP.2009.5347726

Filename

5347726