Ultra Local Nonlinear Unknown Input Observers for Robust Fault Reconstruction

Farhad Ghanipoor; Carlos Murguia; Peyman Mohajerin Esfahani; Nathan van de Wouw

doi:10.1109/CDC51059.2022.9992945

Ultra Local Nonlinear Unknown Input Observers for Robust Fault Reconstruction

Farhad Ghanipoor, Carlos Murguia, Peyman Mohajerin Esfahani, Nathan van de Wouw

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

4 Citations (Scopus)

Abstract

In this paper, we present a methodology for actuator and sensor fault estimation in nonlinear systems. The method consists of augmenting the system dynamics with an approximated ultra-local model (a finite chain of integrators) for the fault vector and constructing a Nonlinear Unknown Input Observer (NUIO) for the augmented dynamics. Then, fault reconstruction is reformulated as a robust state estimation problem in the augmented state (true state plus fault-related state). We provide sufficient conditions that guarantee the existence of the observer and stability of the estimation error dynamics (asymptotic stability of the origin in the absence of faults and ISS guarantees in the faulty case). Then, we cast the synthesis of observer gains as a semidefinite program where we minimize the ℒ2-gain from the model mismatch induced by the approximated fault model to the fault estimation error. Finally, simulations are given to illustrate the performance of the proposed methodology.

Original language	English
Title of host publication	2022 IEEE 61st Conference on Decision and Control, CDC 2022
Publisher	Institute of Electrical and Electronics Engineers
Chapter	9992945
Pages	918-923
Number of pages	6
ISBN (Electronic)	9781665467612
DOIs	https://doi.org/10.1109/CDC51059.2022.9992945
Publication status	Published - 10 Jan 2023
Event	61st IEEE Conference on Decision and Control, CDC 2022 - The Marriott Cancún Collection, Cancun, Mexico Duration: 6 Dec 2022 → 9 Dec 2022 Conference number: 61 https://cdc2022.ieeecss.org/

Conference

Conference	61st IEEE Conference on Decision and Control, CDC 2022
Abbreviated title	CDC 2022
Country/Territory	Mexico
City	Cancun
Period	6/12/22 → 9/12/22
Internet address	https://cdc2022.ieeecss.org/

Funding

This publication is part of the project Digital Twin project 4.3 with project number P18-03 of the research programme Perspectief which is (mainly) financed by the Dutch Research Council (NWO).

Funders	Funder number
Nederlandse Organisatie voor Wetenschappelijk Onderzoek

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10.1109/CDC51059.2022.9992945

Cite this

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title = "Ultra Local Nonlinear Unknown Input Observers for Robust Fault Reconstruction",

abstract = "In this paper, we present a methodology for actuator and sensor fault estimation in nonlinear systems. The method consists of augmenting the system dynamics with an approximated ultra-local model (a finite chain of integrators) for the fault vector and constructing a Nonlinear Unknown Input Observer (NUIO) for the augmented dynamics. Then, fault reconstruction is reformulated as a robust state estimation problem in the augmented state (true state plus fault-related state). We provide sufficient conditions that guarantee the existence of the observer and stability of the estimation error dynamics (asymptotic stability of the origin in the absence of faults and ISS guarantees in the faulty case). Then, we cast the synthesis of observer gains as a semidefinite program where we minimize the ℒ2-gain from the model mismatch induced by the approximated fault model to the fault estimation error. Finally, simulations are given to illustrate the performance of the proposed methodology.",

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Ghanipoor, F, Murguia, C, Mohajerin Esfahani, P & van de Wouw, N 2023, Ultra Local Nonlinear Unknown Input Observers for Robust Fault Reconstruction. in 2022 IEEE 61st Conference on Decision and Control, CDC 2022. Institute of Electrical and Electronics Engineers, pp. 918-923, 61st IEEE Conference on Decision and Control, CDC 2022, Cancun, Mexico, 6/12/22. https://doi.org/10.1109/CDC51059.2022.9992945

Ultra Local Nonlinear Unknown Input Observers for Robust Fault Reconstruction. / Ghanipoor, Farhad; Murguia, Carlos; Mohajerin Esfahani, Peyman et al.
2022 IEEE 61st Conference on Decision and Control, CDC 2022. Institute of Electrical and Electronics Engineers, 2023. p. 918-923.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Ultra Local Nonlinear Unknown Input Observers for Robust Fault Reconstruction

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