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Plug-and-Play Fault Detection and Isolation for Large-Scale Nonlinear Systems with Stochastic Uncertainties

Boem, F; Riverso, S; Ferrari-Trecate, G; Parisini, T; (2019) Plug-and-Play Fault Detection and Isolation for Large-Scale Nonlinear Systems with Stochastic Uncertainties. IEEE Transactions on Automatic Control , 64 (1) pp. 4-19. 10.1109/TAC.2018.2811469. Green open access

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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.

Type: Article
Title: Plug-and-Play Fault Detection and Isolation for Large-Scale Nonlinear Systems with Stochastic Uncertainties
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TAC.2018.2811469
Publisher version: http://dx.doi.org/10.1109/TAC.2018.2811469
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10046398
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