Cart (Loading....) | Create Account
Close category search window
 

Diagonal Recurrent Neural Network as an On-line Identifier for a Cold Flow Circulating Fluidized Bed

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

4 Author(s)
Caswell, W.A. ; MS Control Syst., WVUIT WV, Montgomery, WV ; Davari, A. ; Bao Liu ; Shadle, L.

Circulating fluidized beds (CFB) are widely used in energy industries for increasing the efficiency and reducing environment pollution. CFB modeling and identification have significant importance for operation optimization. Owing to the nonlinear nature of CFB operation, online CFB modeling and identification are highly desirable so that the model can adjust itself according to the change of CFB operation. In this paper, we develop an online CFB identification method based on diagonal recurrent neural network (DRNN) modeling. This method was applied to a large-scale cold flow CFB at the National Energy Technology Laboratory for prediction of solid circulation rate. The result showed that this method worked excellently.

Published in:

System Theory, 2007. SSST '07. Thirty-Ninth Southeastern Symposium on

Date of Conference:

4-6 March 2007

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.