Proximal-based recursive implementation for model-free data-driven fault diagnosis

DOI10.1016/j.automatica.2024.111656zbMATH Open1545.93101MaRDI QIDQ6566741

Oleg A. Soloviev, Jacques Noom, Michel Verhaegen

Publication date: 3 July 2024

Published in: Automatica (Search for Journal in Brave)

zbMATH Keywords

system identificationfault detection and isolation

Mathematics Subject Classification ID

System identification (93B30) Linear systems in control theory (93C05)

Cites Work

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• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• A three-operator splitting scheme and its optimization applications
• Model-based fault diagnosis techniques. Design schemes, algorithms and tools
• The generalized Lasso problem and uniqueness
• The role of vector autoregressive modeling in predictor-based subspace identification
• A Generalized Forward-Backward Splitting
• Proximal Splitting Methods in Signal Processing
• A Singular Value Thresholding Algorithm for Matrix Completion
• A proximal decomposition method for solving convex variational inverse problems
• Filtering and System Identification
• Online Learning With Inexact Proximal Online Gradient Descent Algorithms
• Data-Driven Fault Detection for Industrial Processes
• Dynamic System Fault Diagnosis Under Sparseness Assumption
• Diagnosis and Fault-Tolerant Control
• Signal Recovery by Proximal Forward-Backward Splitting

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