DocumentCode
3358193
Title
Robust speed estimation of an asynchronous machine aided by a dynamic neural network
Author
Ghouili, J. ; Chériti, A.
Author_Institution
Ecole d´´Ingenierie, Groupe de Recherche en Electron. Ind., Trois-Rivieres, Que., Canada
Volume
2
fYear
1999
fDate
9-12 May 1999
Firstpage
1086
Abstract
This article presents the estimation of angular velocity of an asynchronous machine aided by an artificial neural network. The input variables of the network are utilised as outputs for a stationary reference point of the stator. They are compared, according to the topologies considered, of voltages, currents, and instantaneous active and reactive power consumed by the machine, and speed feedback. As a result of modelling the machine and using the neural network, different estimators are proposed, studied and characterised. Analysis of the simulation results obtained with the aid of Simulink Toolbox and Nnet confirm the performance of the estimators studied.
Keywords
angular velocity; asynchronous machines; electric machine analysis computing; neural nets; parameter estimation; Nnet; Simulink Toolbox; angular velocity estimation; asynchronous machine; currents; dynamic neural network; input variables; instantaneous active power; instantaneous reactive power; robust speed estimation; speed feedback; stationary reference point; voltages; Angular velocity; Artificial neural networks; Input variables; Network topology; Neural networks; Neurofeedback; Reactive power; Robustness; Stators; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Computer Engineering, 1999 IEEE Canadian Conference on
Conference_Location
Edmonton, Alberta, Canada
ISSN
0840-7789
Print_ISBN
0-7803-5579-2
Type
conf
DOI
10.1109/CCECE.1999.808202
Filename
808202
Link To Document