DocumentCode
287259
Title
Neural networks used for torque ripple minimisation from a switched reluctance motor
Author
Reay, D.S. ; Green, T.C. ; Williams, B.W.
Author_Institution
Heriot-Watt Univ., UK
fYear
1993
fDate
13-16 Sep 1993
Firstpage
1
Abstract
The application of neural techniques to the problem of torque ripple minimisation in a switched reluctance motor (SRM) is presented. More conventional techniques for torque linearisation and decoupling are reviewed, after which the application of a neural network to the problem is described. Results obtained experimentally and by simulation of a 4 kW IGBT power converter and 4-phase SRM are used to illustrate the approach. The networks used have been implemented using both digital signal processor (DSP) and field programmable gate array (FPGA) technologies
Keywords
digital control; insulated gate bipolar transistors; machine control; neural nets; optimal control; power convertors; power transistors; reluctance motors; switching circuits; torque control; 4 kW; IGBT power converter; SRM; application; decoupling; digital control; digital signal processor; field programmable gate array; linearisation; machine control; neural network; optimal control; power transistors; switched reluctance motor; torque control; torque ripple minimisation;
fLanguage
English
Publisher
iet
Conference_Titel
Power Electronics and Applications, 1993., Fifth European Conference on
Conference_Location
Brighton
Type
conf
Filename
264969
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