By Topic

Optimal fuzzy pid controller design of an active magnetic bearing system based on adaptive genetic algorithms

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)
Hung-Cheng Chen ; Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung, Taiwan

This paper proposes an adaptive genetic algorithm (AGA) for the multi-objective optimization design of a fuzzy PID controller and applies it to the control of an active magnetic bearing (AMB) system. Different from PID controllers with fixed gains, the fuzzy PID controller is expressed in terms of fuzzy rules whose rule consequences employ analytical PID expressions. The PID gains are adaptive and the fuzzy PID controller has more flexibility and capability than the conventional ones. Moreover, it can be easily utilized to develop a precise and fast control algorithm in optimal design. An adaptive genetic algorithm is proposed to design the fuzzy PID controller. The centers of the triangular membership functions and the PID gains for all fuzzy control rules are selected as parameters to be determined. The dynamic model of AMB system for axial motion is also presented. The simulation results of this AMB system show that a fuzzy PID controller designed via the proposed AGA has good performance.

Published in:

2008 International Conference on Machine Learning and Cybernetics  (Volume:4 )

Date of Conference:

12-15 July 2008