NDLI: Fuzzy integrated process supervision

Content Provider	IEEE Xplore Digital Library
Author	Quek, C. Ng, P.W.
Copyright Year	1996
Description	Author affiliation: Intelligent Syst. Lab., Nanyang Technol. Inst., Singapore (Quek, C.)
Abstract	The integrated process supervision (IFS) is a structured refinement of the expert control architecture that allows the integration of different control techniques within a single generic framework. This is achieved in IFS through the classification of system behaviour into acceptable, malfunction and faulty behaviours according to certain system performance measurement using a simple thresholding, detection mechanism. This technique raises two important research issues, namely, the choice of the thresholds between the classes of system behaviours, and the sensitivity of such thresholding mechanism to uncertainty and noise during the determination, of system behaviours. This paper attempts to address the second issue by using fuzzy sets instead of crisp behaviour categorisation to represents system behaviours. Extensive experimental results have shown that the use of fuzzy sets provides significant noise tolerance in the switching mechanism and improves the transparency of the integrated process supervisor, as well as the modularity of the IFS scheme.
Starting Page	319
Ending Page	324
File Size	646185
Page Count	6
File Format	PDF
ISBN	0780329783
ISSN	21589860
DOI	10.1109/ISIC.1996.556221
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-09-15
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Control systems Knowledge based systems Fault diagnosis Fuzzy sets Noise shaping Control engineering Safety Logic Diagnostic expert systems Intelligent systems
Content Type	Text
Resource Type	Article

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