Plug-and-play fault detection and isolation for large-scale nonlinear systems with stochastic uncertainties

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Title: Plug-and-play fault detection and isolation for large-scale nonlinear systems with stochastic uncertainties
Authors: Boem, F
Riverso, S
Ferrari-Trecate, G
Parisini, T
Item Type: Journal Article
Abstract: This paper proposes a novel scalable model-based fault detection and isolation approach for the monitoring of nonlinear large-scale systems, consisting of a network of interconnected subsystems. The fault diagnosis architecture is designed to automatically manage the possible plug-in of novel subsystems and unplugging of existing ones. The reconfiguration procedure involves only local operations and communication with neighboring subsystems, thus, yielding a distributed and scalable architecture. In particular, the proposed fault diagnosis methodology allows the unplugging of faulty subsystems in order to possibly avoid the propagation of faults in the interconnected large-scale system. Measurement and process uncertainties are characterized in a probabilistic way leading to the computation, at each time-step, of stochastic time-varying detection thresholds with guaranteed false-alarms probability levels. To achieve this goal, we develop a distributed state estimation scheme, using a consensus-like approach for the estimation of variables shared among more than one subsystem; the time-varying consensus weights are designed to allow plug-in and unplugging operations and to minimize the variance of the uncertainty of the fault diagnosis thresholds. Convergence results of the distributed estimation scheme are provided. A novel fault isolation method is then proposed, based on a generalized observer scheme and providing guaranteed error probabilities of the fault exclusion task. Detectability and isolability conditions are provided. Simulation results on a power network model comprising 15 generation areas show the effectiveness of the proposed methodology.
Issue Date: Jan-2019
Date of Acceptance: 1-Feb-2018
ISSN: 0018-9286
Publisher: Institute of Electrical and Electronics Engineers
Start Page: 4
End Page: 19
Journal / Book Title: IEEE Transactions on Automatic Control
Volume: 64
Issue: 1
Copyright Statement: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Commission of the European Communities
Funder's Grant Number: EP/L014343/1
Keywords: Science & Technology
Automation & Control Systems
Engineering, Electrical & Electronic
Fault detection
interconnected systems
large-scale systems
nonlinear systems
stochastic systems
systems of systems
0906 Electrical and Electronic Engineering
0102 Applied Mathematics
0913 Mechanical Engineering
Industrial Engineering & Automation
Publication Status: Published
Online Publication Date: 2018-03-01
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering

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