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Yousfi B, Raïssi T, Amairi M, et al. Set-membership methodology for model-based prognosis. ISA Trans. 2016;66:216-225doi: 10.1016/j.isatra.2016.09.025.
Yousfi, B., Raïssi, T., Amairi, M., & Aoun, M. (2017). Set-membership methodology for model-based prognosis. ISA transactions, 66216-225. https://doi.org/10.1016/j.isatra.2016.09.025
Yousfi, Basma, et al. "Set-membership methodology for model-based prognosis." ISA transactions vol. 66 (2017): 216-225. doi: https://doi.org/10.1016/j.isatra.2016.09.025
Yousfi B, Raïssi T, Amairi M, Aoun M. Set-membership methodology for model-based prognosis. ISA Trans. 2017 Jan;66:216-225. doi: 10.1016/j.isatra.2016.09.025. Epub 2016 Oct 21. PMID: 27776742.
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ISA Trans. 2017 Jan;66:216-225. doi: 10.1016/j.isatra.2016.09.025. Epub 2016 Oct 21.

Set-membership methodology for model-based prognosis.

ISA transactions

Basma Yousfi, Tarek Raïssi, Messaoud Amairi, Mohamed Aoun

Affiliations

  1. MACS Laboratory : Modeling, Analysis and Control of Systems LR16ES22, National Engineering School of Gabes (ENIG), University of Gabes, Tunisia.. Electronic address: [email protected].
  2. Conservatoire National des Arts et Métiers (CNAM), Cedric-Lab. 292, Rue St-Martin, 75141 Paris Cedex 03, France. Electronic address: [email protected].
  3. MACS Laboratory : Modeling, Analysis and Control of Systems LR16ES22, National Engineering School of Gabes (ENIG), University of Gabes, Tunisia.. Electronic address: [email protected].
  4. MACS Laboratory : Modeling, Analysis and Control of Systems LR16ES22, National Engineering School of Gabes (ENIG), University of Gabes, Tunisia.. Electronic address: [email protected].

PMID: 27776742 DOI: 10.1016/j.isatra.2016.09.025

Abstract

This paper addresses model-based prognosis to predict Remaining Useful Life (RUL) of a class of dynamical systems. The methodology is based on singular perturbed techniques to take into account the slow behavior of degradations. The full-order system is firstly decoupled into slow and fast subsystems. An interval observer is designed for both subsystems under the assumption that the measurement noise and the disturbances are bounded. Then, the degradation is modeled as a polynomial whose parameters are estimated using ellipsoid algorithms. Finally, the RUL is predicted based on an interval evaluation of the degradation model over a time horizon. A numerical example illustrates the proposed technique.

Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Keywords: Damage; Interval observers; Prognosis; Remaining useful life; Singularly perturbed systems

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