By Topic

Neural network approach to variable structure based adaptive tracking of SISO systems

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
$33 $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

1 Author(s)
Li-Chen Fu ; Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan

This paper presents a novel approach to adaptive tracking control of linear SISO systems, which can solve the traditional model reference adaptive control (MRAC) problems. In this approach, a neural network universal approximator is included to furnish an online estimate of a function of the state and some signals relevant to the desired trajectory. The salient feature of the present work is that a rigorous proof via Lyapunov stability theory is provided. It is shown that the output error will fall into a residual set which can be made arbitrarily small

Published in:

Variable Structure Systems, 1996. VSS '96. Proceedings., 1996 IEEE International Workshop on

Date of Conference:

5-6 Dec 1996