By Topic

Synchronization method with variable sampling frequency using Neuronal Networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Carugati, I. ; Univ. Nat. de Mar del Plata, Mar del Plata, Argentina ; Maestri, S. ; Donato, P.G. ; Carrica, D.
more authors

This article presents a alternative synchronization method for three phase systems based on Artificial Neuronal Networks. The training signals are obtained from a synchronism method designed with a conventional control whose objective is to achieve a sampling frequency at a N times higher frequency with regard to the input signals. As a consequence of the complexity of the system, it is modelled with two different neural networks. The objective of the first one is to estimate the input signal phase and the objective of the second one is to generate a variable sampling frequency. The system is evaluated with typical disturbances, obtaining a similar behaviour in comparison with the conventional system. MATLAB simulations results are presented.

Published in:

Latin America Transactions, IEEE (Revista IEEE America Latina)  (Volume:9 ,  Issue: 5 )