By Topic

A Comparison of Mandani and Sugeno Inference Systems for a Space Fault Detection Application

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

4 Author(s)
J. J. Jassbi ; Azad University, Science and Research Campus, Iran, ; Paulo J. A. Serra ; Rita A. Ribeiro ; Alessandro Donati

This research provides a comparison between the performances of TSK (Takagi, Sugeno, Kang)-type versus Mandani-type fuzzy inference systems. The main motivation behind this research was to assess which approach provides the best performance for a gyroscope fault-detection application, developed in 2002 for the European Space Agency (ESA) satellite ENVISAT. Due to the importance of performance in online systems we compare the application, developed with Mamdani model, with a TSK formulation using three types of tests: processing time for both systems, robustness in the presence of randomly generated noise; and sensitivity analysis of the systems' behaviors to changes in input data. The results show that the TSK model perform better in all three tests, hence we may conclude that replacing a Mamdani system with an equivalent TSK system could be a good option to improve the overall performance of a fuzzy inference system.

Published in:

2006 World Automation Congress

Date of Conference:

24-26 July 2006