학술논문
Control system DC motor with speed estimator by neural networks
Document Type
Conference
Author
Source
2005 International Conference on Power Electronics and Drives Systems Wireless Pervasive Computing Power Electronics and Drives Systems, 2005. PEDS 2005. International Conference on. 2:1030-1035 2005
Subject
Language
ISSN
2164-5256
2164-5264
2164-5264
Abstract
This paper introduces the new ability of Artificial Neural Networks (ANNs) in estimating speed and controlling the separately excited DC motor. The neural control scheme consists of two parts. One is the neural estimator which is used to estimate the motor speed. The other is the neural controller which is used to generate a control signal for a converter. These two neurals are training by Levenberg-Marquardt back-propagation algorithm. ANNs are the standard three layers feed-forward neural network with sigmoid activation functions in the input and hidden layers and purelin in the output layer. Simulation result are presented to demonstrate the effectiveness of this neural and advantage of the control system DC motor with ANNs in comparison with the conventional scheme without ANNs.