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 |
Files in This Item:
File | Description | Size | Format | |
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detectable_jrnl.pdf | 131,58 kB | Adobe PDF | View/Open |
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