Model based fault detection of nonlinear systems using singleton interval type-2 fuzzy sets

Author

Ghiasi, T.S. ; Pour, H.Zarabadi ; Shoorehdeli, M. Aliyari

Author_Institution

Eng. Dept., Imam Khomeini Int. Univ. of Qazvin, Qazvin, Iran

fYear

2011

fDate

17-19 May 2011

Firstpage

1

Lastpage

6

Abstract

Fault detection using a novel approach based singleton interval type 2 fuzzy sets is presented in this paper. The main idea of introduced method is based the concept of type-2 fuzzy sets. Residual signal could be constructed using this concept and evaluation of it can be done as well. The benefits of the proposed method have been presented by a well-known benchmark problem. Simulation results depict that the proposed fault detection method is highly effective tool in fast fault detection of nonlinear systems.

Keywords

fuzzy neural nets; fuzzy set theory; neurocontrollers; nonlinear control systems; model based fault detection; nonlinear systems; residual signal; singleton interval type-2 fuzzy sets; type-2 fuzzy neural network; type-2 fuzzy set concept; Estimation; Fault detection; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Mathematical model; Nonlinear systems; Fault Detection; Interval Type-2 Fuzzy; Singleton Type-2 fuzzy; Type-2 Fuzzy Logic system; Type-2 Fuzzy Neural Network;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Engineering (ICEE), 2011 19th Iranian Conference on

Conference_Location

Tehran

Print_ISBN

978-1-4577-0730-8

Electronic_ISBN

978-964-463-428-4

Type

conf

Filename

5955701