Title :
Estimation of electrical machine speed using sensorless technology and neural networks
Author :
Goedtel, A. ; Silva, N. ; Serni, P. ; Suetake, M.
Author_Institution :
Dept. of Electrotech., Univ. of Technol. Parana, Curitiba
Abstract :
The use of sensorless technologies is an increasing tendency on industrial drivers for electrical machines. The estimation of electrical and mechanical parameters involved with the electrical machine control is used very frequently in order to avoid measurement of all variables related to this process. The cost reduction may also be considered in industrial drivers, besides the increasing robustness of the system, as an advantage of the use of sensorless technologies. This work proposes the use of a recurrent artificial neural network to estimate the speed of induction motor for sensorless control schemes using one single current sensor. Simulation and experimental results are presented to validate the proposed approach.
Keywords :
artificial intelligence; electric machine analysis computing; electric machines; machine control; recurrent neural nets; electrical machine control; electrical machine speed estimation; electrical parameter; industrial drivers; mechanical parameter; recurrent artificial neural network; sensorless control schemes; sensorless technology; single current sensor; Artificial neural networks; Costs; Electric variables measurement; Electrical equipment industry; Induction motors; Machine control; Mechanical variables measurement; Neural networks; Robustness; Sensorless control; Induction Motors; Neural Networks; System Identification;
Conference_Titel :
Transmission and Distribution Conference and Exposition: Latin America, 2008 IEEE/PES
Conference_Location :
Bogota
Print_ISBN :
978-1-4244-2217-3
Electronic_ISBN :
978-1-4244-2218-0
DOI :
10.1109/TDC-LA.2008.4641832