By Topic

A novel robust PID controllers design by fuzzy neural network

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)
Ching-Hung Lee ; Dept. of Electr. Eng., Yuan Ze Univ., Taoyuan, Taiwan ; Yi-Hsiung Lee ; Ching-Cheng Teng

In the paper, we propose a robust PID tuning method using fuzzy neural network (FNN) based on robust gain and phase margin (GM/PM) specifications. The designed PID controller is available for the interval plant family. We can use the trained FNN system to determine the parameters of PID controllers that are based on the robust GM/PM. To determine the robust GM/PM, the Kharitonov 32 extreme systems are used. Therefore, the FNN system is able to automatically tune the PID controller parameters with different GM/PM specifications, so that neither numerical methods nor graphical methods have to be used. This makes it easy to tune the controller parameters to have the specified robustness and performance. Simulation results are shown to illustrate the effectiveness of the robust PID controller scheme.

Published in:

American Control Conference, 2002. Proceedings of the 2002  (Volume:2 )

Date of Conference:

2002