Open AccessFault detection for vehicle active suspension systems in finite‐frequency domain
Author(s) -
Zhu Xiaodan,
Xia Yuanqing,
Chai Senchun,
Shi Peng
Publication year - 2019
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.2018.5922
Subject(s) - control theory (sociology) , frequency domain , fault detection and isolation , fault (geology) , kalman filter , lemma (botany) , residual , stability (learning theory) , filter (signal processing) , computer science , filter design , suspension (topology) , engineering , control engineering , mathematics , algorithm , actuator , artificial intelligence , control (management) , seismology , homotopy , pure mathematics , computer vision , geology , ecology , poaceae , machine learning , biology
This study solves a new fault detection strategy for vehicle active suspension systems in finite‐frequency domain. Three fault detection filters are constructed in different finite frequency domains, which ensure that the error between residuals and faults is minimum. The H ∞ filter problem is used to figure out the design problem of fault detection. The conditions of residual systems meeting H ∞ performance are obtained by considering generalised Kalman–Yakubovich–Popov lemma and stability theory. The problem of filter design is solved by an optimisation algorithm. Illustrative examples are given to show the proposed design method's effectiveness and potential.