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

Stable Adaptive Neural Network Control of Nonaffine Nonlinear Discrete-Time Systems and Application

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

3 Author(s)
Lianfei Zhai ; Northeastern Univ., Shenyang ; Tianyou Chai ; Shuzhi Sam Ge

Both state and output feedback adaptive neural network controls are developed for a class of discrete-time single-input single-output (SISO) nonaffine uncertain nonlinear systems. Each controller incorporates a linear dynamic compensator and an adaptive neural network term. The linear dynamic compensator is designed to stabilize the linearized system, and the adaptive neural network term is introduced to deal with nonlinearity. The closed-loop systems are proved to be semi-globally uniformly ultimately bounded (SGUUB) by using linear matrix inequality (LMI). Simulation of a liquid level system illustrates the effectiveness of proposed controls.

Published in:

Intelligent Control, 2007. ISIC 2007. IEEE 22nd International Symposium on

Date of Conference:

1-3 Oct. 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.