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

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4 Author(s)

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:

Automation Congress, 2006. WAC '06. World

Date of Conference:

24-26 July 2006