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Robust Analytical Redundancy Relations for Fault Diagnosis In Nonlinear Systems
Author(s) -
Shumsky Alexey
Publication year - 2002
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1111/j.1934-6093.2002.tb00342.x
Subject(s) - redundancy (engineering) , nonlinear system , control theory (sociology) , observable , fault detection and isolation , computer science , robustness (evolution) , mathematics , algorithm , artificial intelligence , operating system , biochemistry , chemistry , physics , control (management) , quantum mechanics , gene
The problem of robust analytical redundancy relations design for fault diagnosis in nonlinear systems is investigated. An approach is proposed to solve this problem through an extension of the system state‐space by means of constant (or slow varying) unknown parameters, followed by designing analytical redundancy relations that are insensitive both to state variables and unknown parameters. To make the design practicable, some problems related to nonlinear transformation of the extended system model into observable one are considered. The quasi‐linear computational form for robust analytical redundancy relations is described. Fault detectability and distinguishability conditions are formulated, and a recommendation for choosing the size of the moving time window is made. The results are demonstrated through an example involving an SISO nonlinear model of an underwater vehicle.