An improved particle filtering-based approach for health prediction and prognosis of nonlinear systems

DOI10.1016/j.jfranklin.2018.02.023zbMath1390.93783OpenAlexW2789350723MaRDI QIDQ1643237

Najmeh Daroogheh, Khashayar Khorasani, Nader Meskin

Publication date: 19 June 2018

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://spectrum.library.concordia.ca/983568/1/An%20Improved%20Particle%20Filtering-based%20Approach%20for%20Health%20Prediction%20and%20Prognosis%20of%20Nonlinear%20Systems.pdf

zbMATH Keywords

nonlinear systemshealth monitoringuncertainty managementestimation and prediction schemesMahalanobis distance criterionparticle filter (PF)sliding observation injection window

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Nonlinear systems in control theory (93C10) Control/observation systems with incomplete information (93C41) Estimation and detection in stochastic control theory (93E10)

Cites Work

• Bayesian forecasting and dynamic models.
• Complexity analysis of the marginalized particle filter
• Matrix Equation $XA + BX = C$
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: An improved particle filtering-based approach for health prediction and prognosis of nonlinear systems