By Topic

Enhancing the performance of a multivariable fuzzy controller by means of multiobjective genetic programming and statistical analysis

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)
Bica, B. ; Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, UK ; Chipperfield, A.J. ; Fleming, P.J. ; MacKenzie, S.

The paper addresses the issue of performance optimisation of a MIMO fuzzy controller for a gas turbine aero-engine. The proposed method attempts to improve the performance of the controller by looking at the accuracy of the input-output mapping of the control parameters. A multiobjective genetic programming approach is utilized to search for suitable input-output structures, able to satisfy the rigorous performance criteria imposed on military engines and simultaneously to ensure the accuracy of the output surfaces. The effectiveness of the approach is verified by performing statistical tests of significance on the design data. In an effort to reduce the computational burden associated with controller design via optimisation, a response surface method is also considered

Published in:

Industrial Electronics Society, 2000. IECON 2000. 26th Annual Confjerence of the IEEE  (Volume:1 )

Date of Conference:

2000