Chapter 5

system. International Journal of Machine Learning and Cybernetics. 2012;3(1):1-26. DOI: 10.1007/

Fault Detection, Diagnosis and Prognosis

[16] Jun W, Shitong W, Chung F-L. Positive and negative fuzzy rule system, extreme learning machine and image classification. International Journal of Machine Learning and Cybernetics. 2011;2(4):261-271. DOI: 10.1007/

[17] Fantuzzi C, Simani S, Beghelli S, Rovatti R. Identification of piecewise affine models in noisy environment. International Journal of Control. 2002; 75(18):1472-1485. DOI: 10.1109/

[18] Haykin S. Kalman Filtering and Neural Networks, Adaptive and

Wiley & Sons, Inc; 2001

Learning Systems for Signal Processing, Communications, and Control. New York, USA: Wiley–Interscience, John

[19] Xu J-X, Liu C, Hang C. Combined adaptive and fuzzy control using multiple models. In: Proceedings of Third IEEE International Conference on Fuzzy Systems, Orlando, FL. 1994

[20] Hunt K, Sbarbaro D, Zbikowki R, Gawthrop P. Neural networks for control system: A survey. IEEE

Transactions on Neural Networks. 1992;

[21] Simani S, Farsoni S, Castaldi P. Fault diagnosis of a wind turbine benchmark via identified fuzzy models. IEEE Transactions on Industrial Electronics. 2015;62(6):3775-3782. Invited paper for the special issue "Real–time fault diagnosis and fault tolerant control". DOI: 10.1109/TIE.2014.2364548

[22] Ding SX. Model–Based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools. 1st ed. Berlin Heidelberg: Springer; 2008. ISBN:

s13042-011-0041-0

s13042-011-0024-1

87.865858

28:1083-1112

978–3540763031

64
