Open AccessIncipient fault diagnosis for T–S fuzzy systems with application to high‐speed railway traction devices
Author(s) -
Wu Yunkai,
Jiang Bin,
Shi Peng
Publication year - 2016
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2015.1320
Subject(s) - fault detection and isolation , residual , actuator , control theory (sociology) , fault (geology) , traction control system , fuzzy logic , computer science , control engineering , traction (geology) , fuzzy control system , engineering , automotive engineering , artificial intelligence , control (management) , algorithm , mechanical engineering , seismology , geology
This study addresses the problem of incipient fault detection and diagnosis for Takagi–Sugeno (T–S) fuzzy systems and explores further results of total measurable fault information residual (ToMFIR). First, T–S fuzzy model is used to describe the global dynamics of a non‐linear system and the model of incipient actuator faults is formalised. Second, based on the ToMFIR, a novel incipient fault detection method is proposed, which removes the assumptions on system structure in some existing work. Further, sliding‐mode observers combined with ToMFIR‐based thresholds are designed for incipient fault isolation. Finally, application results conducted on a high‐speed railway traction device are given to illustrate the effectiveness of the proposed approach.