Fuzzy Filter-Based FDD Design for Non-Gaussian Stochastic Distribution Processes Using T-S Fuzzy Modeling

Mathematical Problems in Engineering. 2013;2013 DOI 10.1155/2013/156262

 

Journal Homepage

Journal Title: Mathematical Problems in Engineering

ISSN: 1024-123X (Print); 1563-5147 (Online)

Publisher: Hindawi Publishing Corporation

LCC Subject Category: Technology: Engineering (General). Civil engineering (General) | Science: Mathematics

Country of publisher: Egypt

Language of fulltext: English

Full-text formats available: PDF, HTML, ePUB, XML

 

AUTHORS

Yang Yi (College of Information Engineering, Yangzhou University, Yangzhou 225127, China)
Yue-Yue Zhao (College of Information Engineering, Yangzhou University, Yangzhou 225127, China)
Song-Yin Cao (College of Information Engineering, Yangzhou University, Yangzhou 225127, China)

EDITORIAL INFORMATION

Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 26 weeks

 

Abstract | Full Text

This paper studies the fuzzy modeling problem and the fault detection and diagnosis (FDD) algorithm for non-Gaussian stochastic distribution systems based on the nonlinear fuzzy filter design. Following spline function approximation for output probability density functions (PDFs), the T-S fuzzy model is built as a nonlinear identifier to describe the dynamic relationship between the control input and the weight vector. By combining the designed filter and the threshold value, the fault in T-S weight model can be detected and the stability of error system can also be guaranteed. Moreover, the novel adaptive fuzzy filter based on stochastic distribution function is designed to estimate the size of system fault. Finally, the simulation results can well verify the effectiveness of the proposed algorithm for the constant fault and the time-varying fault, respectively.