Robust fault detection using neuro-fuzzy networks

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 16, Issue , 2005, Pages 185-190

  Kowal, Marek ^a   Korbicz, Józef ^a  

^a UNIVERSITY OF ZIELONA GÓRA   (Poland)

Author keywords

Bounded noise; Fault detection; Fuzzy modelling; Uncertainty

Indexed keywords

FUZZY INFERENCE; FUZZY NEURAL NETWORKS; SUGAR FACTORIES; SUGAR INDUSTRY; UNCERTAINTY ANALYSIS;

BOUNDED NOISE; FUZZY MODELLING; NEURO-FUZZY MODEL; NEURO-FUZZY NETWORK; ROBUST FAULT DETECTION; TECHNICAL INSTALLATION; UNCERTAINTY;

FAULT DETECTION;

EID: 79960718984     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3182/20050703-6-cz-1902.01833     Document Type: Conference Paper

References (13)

1. Babuska, R. (1998). Fuzzy modeling for control. Kluwer Academic Publisher.
2. Chiu, S. (1994). Fuzzy model identification based on cluster estimation. Journal of Intelligent and Fuzzy Systems.
3. Kang, S-J., C-H. Woo, H-S. Hwang and K. B. Woo (2000). Evolutionary design of fuzzy rule base for nonlinear system modeling and control. IEEE Tran. on Fuzzy Systems 8(1), pp. 37- 45.
4. Korbicz, J., Kościelny J. M., Kowalczuk Z. and Cholewa W. (2004). Fault diagnosis. Models, Artificial Intelligence, Applications. Heidelberg: Springer-Verlag. Berlin.
5. Milanese, M., J. P. Norton, H. Piet-Lahanier and E. Walter (1996). Bounding approaches to identification. Plenum Press. New York.
6. Nelles, O. (2001). Nonlinear System Identification. Springer-Verlag. Berlin.
7. Patton, R. and J. Korbicz (1999). Advances in computational intelligence for fault diagnosis systems. Special issue of Int. J. Appl. Math and Comp. Sci.
8. Patton, R. J. and J. Chen (1999). Robust Model-Based Fault Diagnosis for Dynamic Systems. Kluwer Academic Publishers. London.
9. Rutkowska, D. (2002). Neuro-Fuzzy Architectures and Hybryd Learning. Springer-Verlag, Physica-Verlag. New York.
10. Rutkowska, D. and L. Zadeh (2000). Neuro-fuzzy and soft computing. Special issue of Int. J. Appl. Math and Comp. Sci.
11. Rutkowski, L. (2004). New Soft Computing Techniques for System Modelling, Pattern Classification and Image Processing. Heidelber: Springer-Verlag. Berlin.
12. Soderstrom, T. and P. Stoica (1994). System Identification. Parentice Hall.
13. Walter, E. and L. Pronzato (1997). Identification of Parametric Models from Experimental Data. Springer-Verlag.