Title :
A neural network vector control of induction motor
Author :
Mohamed, H.A.F. ; Hew, W.P.
Author_Institution :
Dept. of Electr. Eng., Malaya Univ., Kuala Lumpur, Malaysia
Abstract :
This paper presents the practical implementation of a computer based slip frequency vector control scheme of an induction motor. A recurrent artificial neural network is used to transform the input parameters, speed error and rate of change of speed error, into an output quantity, the change in inverter output frequency. The recurrent neural network used has an output layer, an input layer and no hidden layer. A novel learning algorithm called the vector space searching algorithm is used to update the network weight. The control algorithm was coded in C++ and implemented on a 486 personal computer
Keywords :
control system synthesis; digital control; induction motors; learning (artificial intelligence); machine testing; machine theory; machine vector control; neurocontrollers; power engineering computing; recurrent neural nets; slip (asynchronous machines); velocity control; 486 personal computer; C++; control algorithm; control design; control performance; induction motor; input layer; input parameters; inverter output frequency change; learning algorithm; neural network vector control; output layer; recurrent artificial neural network; slip frequency vector control scheme; speed error; speed error change rate; vector space searching algorithm; Artificial neural networks; Computer errors; Frequency; Induction motors; Inverters; Machine vector control; Microcomputers; Neural networks; Recurrent neural networks; Weight control;
Conference_Titel :
TENCON 2000. Proceedings
Conference_Location :
Kuala Lumpur
Print_ISBN :
0-7803-6355-8
DOI :
10.1109/TENCON.2000.892285
