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

Fractional Order Periodic Adaptive Learning Compensation for State-Dependent Periodic Disturbance

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)
Ying Luo ; Dept. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou, China ; Yang Quan Chen ; Hyo-Sung Ahn ; You Guo Pi

In this brief, a fractional order periodic adaptive learning compensation (FO-PALC) method is devised for the general state-dependent periodic disturbance minimization on the position and velocity servo platform. In the first trajectory period of the proposed FO-PALC scheme, a fractional order adaptive compensator is designed which can guarantee the boundedness of the system state, input and output signals. From the second repetitive trajectory period and onward, one period previously stored information along the state axis is used in the current adaptation law. Asymptotical stability proof of the system with the proposed FO-PALC is presented. Experimental validation is demonstrated to show the benefits from using fractional calculus in periodic adaptive learning compensation for the state-dependent periodic disturbance.

Published in:

Control Systems Technology, IEEE Transactions on  (Volume:20 ,  Issue: 2 )

Date of Publication:

March 2012

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.