Direct torque control of induction motor by use of neural network

Author

Yourui, Huang ; Chaoli, Tang

Author_Institution

Anhui Univ. of Sci. & Technol.

Volume

3

fYear

2005

fDate

29-29 Sept. 2005

Firstpage

2415

Abstract

General mapping regressor neural network is an incremental self organizing neural network with chains among neurons. This paper deals with the application of the general mapping regressor neural network to the direct torque control of an induction motor. In particular a classical direct torque control strategy has been learnt by the general mapping regressor neural network and then the performance of the neural controller has been verified both in numerical simulations and experimentally by means of a properly devised test bench. The good working of the general mapping regressor neural network has been experimentally verified

Keywords

induction motors; machine testing; machine vector control; neurocontrollers; numerical analysis; self-adjusting systems; torque control; direct torque control; incremental self organizing neural network; induction motor; mapping regressor neural network; neural controller; numerical simulations; test bench; Couplings; Function approximation; Hysteresis motors; Induction motors; Neural networks; Pattern recognition; Pulse width modulation; Stators; Torque control; Voltage control; direct torque control; induction motor; neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Machines and Systems, 2005. ICEMS 2005. Proceedings of the Eighth International Conference on

Conference_Location

Nanjing

Print_ISBN

7-5062-7407-8

Type

conf

DOI

10.1109/ICEMS.2005.203005

Filename

1575202