Data-driven design of fault detection and isolation method for distributed homogeneous systems
type: Item
instance of: scholarly article
title: Data-driven design of fault detection and isolation method for distributed homogeneous systems
zbMATH Open document ID: 1465.93012
author: Xu Yang
author: Jingjing Gao
author: Biao Huang
published in: Journal of the Franklin Institute
publication date: 2021-06-08T00:00:00Z
Mathematics Subject Classification ID: 93A15
Mathematics Subject Classification ID: 93C83
Mathematics Subject Classification ID: 62P30
zbMATH DE Number: 7356372
zbMATH Keywords: data-driven fault detection and isolation
zbMATH Keywords: one-step identification of stable kernel representation
MaRDI profile type: Publication
full work available at URL: j.jfranklin.2021.04.016
OpenAlex ID: W3155800186
cites work: Distributed sensor fault diagnosis for a formation of multi-vehicle systems
cites work: Distributed control design for spatially interconnected systems
cites work: Q4231134
cites work: Simultaneous fault diagnosis for robot manipulators with actuator and sensor faults
cites work: A robust detection and isolation scheme for abrupt and incipient faults in nonlinear systems
cites work: Resilient fault detection observer design of fuzzy Markovian jumping systems with mode-dependent time-varying delays
cites work: Observer-Based Asynchronous Fault Detection for Conic-Type Nonlinear Jumping Systems and its Application to Separately Excited DC Motor
cites work: Geometric properties of partial least squares for process monitoring
cites work: An alternative data-driven fault detection scheme for dynamic processes with deterministic disturbances
cites work: Data-driven realizations of kernel and image representations and their application to fault detection and control system design
cites work: Identification of Fault Estimation Filter From I/O Data for Systems With Stable Inversion
cites work: Dynamic modeling, predictive control and performance monitoring. A data-driven subspace approach
cites work: Subspace Identification of Large-Scale Interconnected Systems
cites work: Subspace Identification of Distributed Clusters of Homogeneous Systems
DOI: 10.1016/J.JFRANKLIN.2021.04.016
description: scientific article; zbMATH DE number 7356372