DocumentCode :
2921454
Title :
Fault diagnosis in a nonlinear three-tank system via ANFIS
Author :
Ucak, Kemal ; Caliskan, Fikret ; Oke, Gulay
Author_Institution :
Dept. of Control Eng., Istanbul Tech. Univ., Istanbul, Turkey
fYear :
2013
fDate :
28-30 Nov. 2013
Firstpage :
566
Lastpage :
570
Abstract :
In this paper, two intelligent methods namely Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS), are implemented to diagnose the leakage faults in a nonlinear three tank system. Two separate structures are utilized for fault diagnosis. One is to identify the dynamics of the plant and the other is to construct the residual logic mechanism. The performance of the proposed methods are evaluated by simulations carried out on a three tank system (TTS). The leakages in tanks are considered as faults in the tank system.
Keywords :
fault diagnosis; fuzzy neural nets; fuzzy reasoning; mechanical engineering computing; nonlinear systems; tanks (containers); ANFIS; adaptive neuro fuzzy inference systems; artificial neural network; intelligent method; leakage fault diagnosis; nonlinear three tank system; plant dynamics; residual logic mechanism; Artificial intelligence; Artificial neural networks; Fault detection; Fault diagnosis; Mathematical model; Nonlinear dynamical systems; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Electronics Engineering (ELECO), 2013 8th International Conference on
Conference_Location :
Bursa
Print_ISBN :
978-605-01-0504-9
Type :
conf
DOI :
10.1109/ELECO.2013.6713910
Filename :
6713910
Link To Document :
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