By Topic

Adaptive fuzzy PID controller based on online LSSVR

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

2 Author(s)
Kemal Ucak ; Department of Control Engineering, Istanbul Technical University, Istanbul, Turkey ; Gulay Oke

In this paper, a predictive adaptation method based on Online Least Square Support Vector Regression (OLSVR) for a fuzzy PID controller has been proposed. Online LSSVR model is utilized to approximate the system Jacobian needed to tune controller parameters. The scaling coefficients of the controller have been tuned depending on K-step ahead future behavior of the system to provide adaptation ability to the controller under changing conditions. Controller parameters are updated using Levenberg Marquard algorithm. The purpose of this paper is to improve the control performance attained by adaptive fuzzy PID which is designed based on the Jacobian information computed by the OLSSVR. The proposed method has been evaluated by simulations carried out on a continuously stirred tank reactor (CSTR), and the results show that the control performance has been improved.

Published in:

Innovations in Intelligent Systems and Applications (INISTA), 2012 International Symposium on

Date of Conference:

2-4 July 2012