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

Adaptive control of arterial blood pressure with a learning controller based on multilayer 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)
Chin-Te Chen ; Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan ; Win-Li Lin ; Te-Son Kuo ; Cheng-Yi Wang

The authors discuss a two-model multilayer neural network controller for adaptive control of mean arterial blood pressure (MABP) using sodium nitroprusside. A model with an autoregressive moving average (ARMA), representing the dynamics of the system, and a modified backpropagation training algorithm are used to design the control system to meet specified objectives of design (settling time and undershoot/overshoot) and clinical constraints. The controller is associated with a weighting-determinant unit (WDU) to determine and update the output weighting factor of the parallel two-model neural network for adequate control action and a control-signal modification unit (CMU) to comply with clinical constraints and to suppress the effect of adverse noise and to improve the WDU performance. Extensive computer simulations indicate satisfactory performance and robustness of the proposed controller in the presence of much noise, over the full range of plant parameters, uncertainties, and large variations of parameters.

Published in:

Biomedical Engineering, IEEE Transactions on  (Volume:44 ,  Issue: 7 )

Date of Publication:

July 1997

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.