FUZZY PATTERN RECOGNITION BASED FAULT DIAGNOSIS

Rafik Bensaadi, Hayet Mouss, Nadia Mouss

2005

Abstract

In order to avoid catastrophic situations when the dynamics of a physical system (entity in a M.A.S architecture) are evolving toward an undesirable operating mode, particular and quick safety actions have to be programmed in the control design. Classic control (PID and even state model based methods) becomes powerless for complex plants (nonlinear, MIMO and ill-defined systems). A more efficient diagnosis requires an artificial intelligence approach. We propose in this paper the design of a Fuzzy Pattern Recognition System (FPRS) that solves, in real time, the main following problems:  Identification of an actual state,  Identification of an eventual evolution towards a failure state,  Diagnosis and decision-making.

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Paper Citation


in Harvard Style

Bensaadi R., Mouss H. and Mouss N. (2005). FUZZY PATTERN RECOGNITION BASED FAULT DIAGNOSIS . In Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 972-8865-19-8, pages 347-356. DOI: 10.5220/0002510403470356


in Bibtex Style

@conference{iceis05,
author={Rafik Bensaadi and Hayet Mouss and Nadia Mouss},
title={FUZZY PATTERN RECOGNITION BASED FAULT DIAGNOSIS},
booktitle={Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2005},
pages={347-356},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002510403470356},
isbn={972-8865-19-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - FUZZY PATTERN RECOGNITION BASED FAULT DIAGNOSIS
SN - 972-8865-19-8
AU - Bensaadi R.
AU - Mouss H.
AU - Mouss N.
PY - 2005
SP - 347
EP - 356
DO - 10.5220/0002510403470356