Open AccessDirectional expansion‐based fault diagnosis algorithm using orthotopic and ellipsoidal filtering
Author(s) -
Liu Zixing,
Wang Ziyun,
Wang Yan,
Park Ju H.,
Ji Zhicheng
Publication year - 2020
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.2020.0029
Subject(s) - ellipsoid , fault (geology) , algorithm , convergence (economics) , set (abstract data type) , fault detection and isolation , bounded function , process (computing) , computer science , mathematics , control theory (sociology) , artificial intelligence , mathematical analysis , physics , actuator , control (management) , astronomy , seismology , economic growth , economics , programming language , geology , operating system
For solving the problem of fault diagnosis for systems with unknown but bounded noises, a directional expansion‐based fault diagnosis algorithm using orthotopic and ellipsoidal filtering is proposed in this study. In this fault diagnosis process, whether the system is faulty or not is checked by detecting whether the ellipsoidal feasible set is empty. When the ellipsoidal feasible set is empty, the specific faulty components are isolated based on the empty state of the test ellipsoidal sets. The orthotopic set is expanded in the faulty directions alone to minimise the set containing the fault parameter vector. Finally, comparative analyses of the proposed fault diagnosis algorithm and global expansion‐based fault diagnosis algorithm using the orthotopic and ellipsoidal filtering in both numerical and case simulations prove the effectiveness and practicability of the proposed algorithm and show the advantages of this algorithm in view of convergence rate and fault identification speed.