By Topic

Identification and control of time-delay system with recurrent wavelet 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

4 Author(s)
Wenjun Zhang ; Navig. Coll., Dalian Maritime Univ., Dalian, China ; Zhengjiang Liu ; Jinshan Zhu ; Xiaoka Xu

A recurrent wavelet neural network (RWNN) is introduced to realize identification and control of system with time delay. The identification is based on model type of nonlinear auto-regressive with exogenous inputs (NARX). The method incorporates the delayed massage of the system, the resulting model can give predictions to the object system. The wavelet-network-based identification model is used for online system identification, and the experiment result of predictive ship course predictive control proved the efficiency of the recurrent neural network model. The identification results are implemented in a control strategy and the simulation result shows the effectiveness of the proposed identification and control method.

Published in:

Intelligent Control and Information Processing (ICICIP), 2012 Third International Conference on

Date of Conference:

15-17 July 2012