Li, P;
Boem, F;
Pin, G;
Parisini, T;
(2019)
Fast-convergent Fault Detection and Isolation in an Uncertain Scenario.
In:
2018 IEEE Conference on Decision and Control (CDC).
(pp. pp. 5544-5549).
IEEE
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Abstract
In this paper, a fast-convergent fault detection and isolation architecture is proposed for linear MIMO continuoustime systems. By exploiting a system decomposition technique and making use of kernel-based deadbeat estimators, the state variables can be estimated in a non-asymptotic way. Estimation residuals are then defined to detect the occurrence of a fault and identify the occurring fault function after fault detection. In the noisy scenario, thresholds are defined for the residual to distinguish the effect of the noise from that of the fault. Numerical examples are included to characterize the effectiveness of the proposed FDI architecture.
| Type: | Proceedings paper |
|---|---|
| Title: | Fast-convergent Fault Detection and Isolation in an Uncertain Scenario |
| Event: | 57th IEEE Conference on Decision and Control, 17-19 December 2018, Miami Beach, FL, USA |
| ISBN-13: | 978-1-5386-1395-5 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/CDC.2018.8618966 |
| Publisher version: | https://doi.org/10.1109/CDC.2018.8618966 |
| 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. |
| Keywords: | Fault detection , Estimation , Kernel , Mathematical model , Fault diagnosis , Convergence , Noise measurement |
| 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/10060824 |
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