Output Behavior Equivalence and Simultaneous Subspace Identification of Systems and Faults
We address the problem of identifying a system subject to additive faults, while simultaneously reconstructing the fault signal via subspace methods. We do not require nominal data for the identification, neither do we impose any assumption on the class of faults, e.g., sensor or actuator faults. We...
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Published in | IEEE control systems letters Vol. 9; pp. 1285 - 1290 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
IEEE
2025
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Online Access | Get full text |
ISSN | 2475-1456 2475-1456 |
DOI | 10.1109/LCSYS.2025.3581870 |
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Abstract | We address the problem of identifying a system subject to additive faults, while simultaneously reconstructing the fault signal via subspace methods. We do not require nominal data for the identification, neither do we impose any assumption on the class of faults, e.g., sensor or actuator faults. We show that, under mild assumptions on the fault signal, standard PI-MOESP can recover the system matrices associated to the input-output subsystem. Then we introduce the concept of output behavior equivalence, which characterizes systems with the same output behavior set, and present a method to establish this equivalence from system matrices. Finally, we show how to estimate from data the complete set of fault matrices for which there exist a fault signal with minimal dimension that explains the data. |
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AbstractList | We address the problem of identifying a system subject to additive faults, while simultaneously reconstructing the fault signal via subspace methods. We do not require nominal data for the identification, neither do we impose any assumption on the class of faults, e.g., sensor or actuator faults. We show that, under mild assumptions on the fault signal, standard PI-MOESP can recover the system matrices associated to the input-output subsystem. Then we introduce the concept of output behavior equivalence, which characterizes systems with the same output behavior set, and present a method to establish this equivalence from system matrices. Finally, we show how to estimate from data the complete set of fault matrices for which there exist a fault signal with minimal dimension that explains the data. |
Author | de Albuquerquer Gleizer, Gabriel |
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Cites_doi | 10.1080/00207179308923017 10.1080/00207179.2017.1286538 10.1016/j.automatica.2010.02.012 10.1109/TAC.2022.3167225 10.1109/TAC.2020.2989269 10.1007/BF01211647 10.1109/TAC.2025.3585652 10.1109/TAC.2017.2742402 10.1007/978-1-4471-2227-2 10.1016/j.jprocont.2013.08.011 10.1016/j.jprocont.2019.08.005 10.1109/78.476442 10.1016/j.conengprac.2015.07.001 10.1137/15M1054201 10.1016/S0005-1098(98)00021-1 10.1016/j.automatica.2024.112049 10.1016/j.automatica.2017.07.040 10.1007/s00034-010-9214-4 10.1109/TAC.2011.2173422 10.1080/00207179.2019.1621385 10.1109/9.73561 10.1016/j.ifacol.2024.07.237 10.1002/acs.1057 10.1017/9781009026338 10.1017/CBO9780511618888 10.1007/978-1-4419-0224-5 |
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Snippet | We address the problem of identifying a system subject to additive faults, while simultaneously reconstructing the fault signal via subspace methods. We do not... |
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SubjectTerms | data-driven modeling Estimation Fault diagnosis Instruments Linear systems Observability Probabilistic logic System identification system realization Training Trajectory |
Title | Output Behavior Equivalence and Simultaneous Subspace Identification of Systems and Faults |
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