Reliable Fault Detection and Diagnosis of Large-Scale Nonlinear Uncertain Systems Using Interval Reduced Kernel PLS

Reliable Fault Detection and Diagnosis of Large-Scale Nonlinear Uncertain Systems Using Interval Reduced Kernel PLS

Kernel partial least squares (KPLS) models are widely used as nonlinear data-driven methods for faults detection (FD) in industrial processes. However, KPLS models lead to irrelevant performance over long operation periods due to process parameters changes, errors and uncertainties associated with m...

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Bibliographic Details
Main Authors: Radhia Fezai, Kamaleldin Abodayeh, Majdi Mansouri, Abdelmalek Kouadri, Mohamed-Faouzi Harkat, Hazem Nounou, Mohamed Nounou, Hassani Messaoud
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Kernel PLS (KPLS)
interval KPLS (IKPLS)
interval reduced KPLS (IRKPLS)
fault detection (FD)
uncertain systems
Online Access:https://ieeexplore.ieee.org/document/9076626/

Internet

https://ieeexplore.ieee.org/document/9076626/

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