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

Mixed Feedforward/Feedback Based Adaptive Fuzzy Control for a Class of MIMO Nonlinear 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
$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

1 Author(s)
Chian-Song Chiu ; Dept. of Electron. Eng., Chien-Kuo Technol. Univ., Changhua

This paper proposes a mixed feedforward/feedback (FFB) based adaptive fuzzy controller design for a class of multiple-input-multiple-output (MIMO) uncertain nonlinear systems. By integrating both feedforward and feedback compensation, we introduce the FFB-based fuzzy controller composed of a feedforward fuzzy compensator and a robust error-feedback compensator. To achieve a forward compensation of uncertainties, the feedforward fuzzy compensator takes the desired commands as premise variables of fuzzy rules and adaptively adjusts the consequent part from an error measure. Meanwhile, the feedback controller part is constructed based on Hinfin control techniques and nonlinear damping design. Then, the attenuation of both disturbances and estimated fuzzy parametric errors is guaranteed from a linear matrix inequality (LMI)-based gain design. The main advantages are: i) a simpler architecture for implementation is provided; and ii) the typical boundedness of assumption on fuzzy universal approximation errors is not required. Finally, an inverted pendulum system and a two-link robot are taken as application examples to show the expected performance

Published in:

Fuzzy Systems, IEEE Transactions on  (Volume:14 ,  Issue: 6 )

Date of Publication:

Dec. 2006

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.