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Robust fault detection and isolation for parameter‐dependent LFT systems
Author(s) -
Cai Xuejing,
Wu Fen
Publication year - 2009
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.1468
Subject(s) - fault detection and isolation , control theory (sociology) , parametric statistics , actuator , observer (physics) , residual , optimization problem , linear matrix inequality , fault (geology) , filter (signal processing) , linear system , computer science , engineering , control engineering , mathematical optimization , mathematics , algorithm , control (management) , statistics , physics , quantum mechanics , artificial intelligence , seismology , computer vision , geology , mathematical analysis
In this paper, we consider robust fault detection and isolation (FDI) problems for faulty linear systems with linear fractional transformation (LFT) parameter dependency and propose an observer‐based solution by using multiobjective optimization techniques. To simplify the design process, a general faulty LFT system will be constructed from the standard LFT description by converting actuator/system component faults into sensor faults first. Then a bank of parameter‐dependent FDI filters will be designed to identify each fault. Each FDI filter will generate a residual signal to track an individual fault with minimum error and to suppress the effects of disturbances, time‐varying parameters and other fault signals. The design of LFT parameter‐dependent FDI filters, as a multiobjective optimization problem, will be formulated in terms of linear matrix inequalities (LMIs) and can be solved efficiently. A numerical example is used to demonstrate the proposed fault detection and isolation approach for LFT systems with different parametric structures. Copyright © 2009 John Wiley & Sons, Ltd.