Title :
A neural network controller for indirect field orientation control
Author :
Mohamadian, M. ; Nowicki, E.P. ; Salmon, J.C.
Author_Institution :
Dept. of Electr. Eng., Calgary Univ., Alta., Canada
Abstract :
This paper presents the design of a neural network controller for the stator current command in an indirect field oriented system. A particular three layer neural network structure is studied in some detail. This neural network controller has two outputs, stationary frame q and d axis current commands iqss and ids s. The input to the neural network are synchronous frame q and d axis current commands, delayed stationary frame q and d axis terminal voltage, rotor speed and delayed values of these parameters. The neural network structure, training and input output selection are discussed. A computer simulation of the closed loop indirect field oriented system with the neural network controller is also presented to verify the feasibility of such a controller
Keywords :
AC motor drives; closed loop systems; controllers; digital simulation; electric machine analysis computing; learning (artificial intelligence); machine control; multilayer perceptrons; neurocontrollers; rotors; stators; closed loop system; computer simulation; d axis current commands; d axis terminal voltage; indirect field orientation control; input output selection; neural network controller; q axis current commands; q axis terminal voltage; rotor speed; stator current command; synchronous frame commands; three layer neural network structure; training; Application software; Artificial neural networks; Biological neural networks; Control systems; Induction motors; Neural networks; Position control; State estimation; Stators; Torque control;
Conference_Titel :
Industry Applications Conference, 1995. Thirtieth IAS Annual Meeting, IAS '95., Conference Record of the 1995 IEEE
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-3008-0
DOI :
10.1109/IAS.1995.530520