Please use this identifier to cite or link to this item: http://hdl.handle.net/11144/3426
Title: Set-based fault detection and isolation for detectable linear parameter-varying systems
Authors: Silvestre, Daniel
Rosa, P.
Hespanha, J.P.
Silvestre, C.
Keywords: fault detection and isolation
unobservable LPV
coprime factorization
distributed
Issue Date: May-2017
Publisher: Wiley
Citation: Silvestre, D., Rosa, P., Hespanha, J. P., and Silvestre, C. (2017) Set-based fault detection and isolation for detectable linear parameter-varying systems. Int. J. Robust. Nonlinear Control, 27: 4381–4397. doi: 10.1002/rnc.3814.
Abstract: In the context of fault detection and isolation of Linear Parameter-Varying (LPV) systems, a challenging task appears when the dynamics and the available measurements render the model unobservable, which invalidates the use of standard Set-Valued Observers (SVOs). Two results are obtained in this paper, namely: using a left-coprime factorization, one can achieve set-valued estimates with ultimately bounded hyper-volume and convergence dependent on the slowest unobservable mode; and, by rewriting the SVO equations and taking advantage of a coprime factorization, it is possible to have a low-complexity fault detection and isolation method. Performance is assessed through simulation, illustrating, in particular, the detection time for various types of faults.
Peer reviewed: yes
URI: http://hdl.handle.net/11144/3426
metadata.dc.identifier.doi: 10.1002/rnc.3814
Appears in Collections:AUTONOMA TECHLAB - Artigos/Papers
DCT - Artigos/Papers

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