DocumentCode :
3066656
Title :
Inverter switching patterns using a neural network
Author :
Kassas, Mahmoud ; Sabbattou, Saleh Zein ; Cook, George E.
Author_Institution :
Dept. of Electr. Eng., Vanderbilt Univ., Nashville, TN, USA
fYear :
1992
fDate :
12-15 Apr 1992
Firstpage :
642
Abstract :
The authors present a method of switching mode selection for a digital current controller using a neural network. The neural network was trained to act as a vector selector for the inverter. The desired voltage vector was calculated from parameters of the induction motor, stator currents, and electromotive force. The backpropagation technique for training neural networks was used based on input/output data obtained from previous simulation studies. The results show excellent correlation between the output of the neural vector selector and the vector selection based on analytical methods. The neural network approach was faster than the previously used analytical methods, making it possible to increase the switching frequency
Keywords :
backpropagation; feedforward neural nets; induction motors; invertors; switching circuits; backpropagation technique; digital current controller; electromotive force; induction motor; inverter; neural network; stator currents; switching mode selection; training; vector selector; voltage vector; Control systems; Current measurement; Frequency estimation; Inverters; Neural networks; Resonance; Stators; Switching frequency; Torque; Voltage control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Southeastcon '92, Proceedings., IEEE
Conference_Location :
Birmingham, AL
Print_ISBN :
0-7803-0494-2
Type :
conf
DOI :
10.1109/SECON.1992.202275
Filename :
202275
Link To Document :
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