Open AccessFuzzy filtering‐based fault detection for a class of discrete‐time conic‐type nonlinear systems
Author(s) -
Wang Jiancheng,
He Shuping
Publication year - 2021
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
eISSN - 1751-9683
pISSN - 1751-9675
DOI - 10.1049/sil2.12016
Subject(s) - conic section , nonlinear system , control theory (sociology) , fuzzy logic , mathematics , filter (signal processing) , linear matrix inequality , fault detection and isolation , fuzzy control system , discrete time and continuous time , type (biology) , fault (geology) , lyapunov function , mathematical optimization , computer science , algorithm , artificial intelligence , control (management) , computer vision , ecology , physics , geometry , quantum mechanics , biology , statistics , seismology , geology
Abstract The authors investigates the problem of fuzzy fault detection filter (FFDF) design for a class of discrete‐time conic‐type nonlinear systems. By applying Takagi–Sugeno fuzzy models, the conic‐type dynamic FFDF system is established. Then, utilizing the Lyapunov function method to find a sufficient condition which ensures that the conic‐type dynamic FFDF system is asymptotically stable. After that, using linear matrix inequalities techniques, the FFDF design problem is transformed into an optimization algorithm. Finally, the simulation results demonstrate that the designed FFDF is effective for detecting the faults.