By Topic

Identification and Control for Discrete Dynamics Systems using Space State Recurrent Fuzzy Neural 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

2 Author(s)
Monroy, P.E.M. ; Univ. Nacional Autonoma de Mexico, Mexico City ; Perez, H.B.

This work presents a structure for modelling and control non linear systems based upon states space recurrent fuzzy neural network (SSRFNN). SSRFNN model has space state structure which is identified since input output data. Fuzzy rules are automatic added through cluster method. Consequent parameter are estimated by using time backpropagation algorithm. An extra observer algorithm is design in order to obtain necessary states measurements. There after control strategy is proposed they some multiple interconnected systems.

Published in:

Electronics, Robotics and Automotive Mechanics Conference, 2007. CERMA 2007

Date of Conference:

25-28 Sept. 2007