Title :
Induction Machine Current Loop Neuro Controller Employing a Lyapunov based Training Algorithm
Author :
Restrepo, J. ; Viola, J. ; Harley, R. ; Habetler, T.
Author_Institution :
Dept. de Electron. y Circuitos, Univ. Simon Bolivar, Caracas
Abstract :
This paper presents a practical implementation of a continually online trained artificial neural network (COT-ANN) employing a Lyapunov based training algorithm. The proposed Lyapunov based training algorithm ensures stability and a global minimum for the ANN weights. The COT-ANN is used to control a PWM based current loop in an induction machine. Real time simulations employing a DSP based test bench are used to test the validity of the algorithm and the results are verified by a practical implementation of this controller.
Keywords :
Lyapunov methods; electric current control; electric machine analysis computing; induction motors; learning (artificial intelligence); machine control; neurocontrollers; pulse width modulation; DSP; Lyapunov-based training algorithm; PWM based control; artificial neural network; continually online training; induction machine current loop controller; neuro controller; real-time simulation; Artificial neural networks; Backpropagation algorithms; Bandwidth; Induction machines; Neurons; Signal processing algorithms; Software algorithms; Stability; Stators; Testing; Backpropagation; Induction motors; Lyapunov methods; Neural Networks;
Conference_Titel :
Power Engineering Society General Meeting, 2007. IEEE
Conference_Location :
Tampa, FL
Print_ISBN :
1-4244-1296-X
Electronic_ISBN :
1932-5517
DOI :
10.1109/PES.2007.385606