Robust fault and icing diagnosis in unmanned aerial vehicles using LPV interval observers
This paper proposes a linear parameter varying (LPV) interval unknown input observer for the robust fault diagnosis of actuator faults and ice accretion in unmanned aerial vehicles (UAVs) described by an uncertain model. The proposed interval observer evaluates the set of values for the state, which...
Published in: | International Journal of Robust and Nonlinear Control |
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Main Authors: | , , , , |
Other Authors: | , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | unknown |
Published: |
John Wiley & Sons
2019
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Subjects: | |
Online Access: | http://hdl.handle.net/10261/202366 https://doi.org/10.1002/rnc.4381 https://doi.org/10.13039/501100011033 https://doi.org/10.13039/501100007273 https://doi.org/10.13039/501100000780 https://doi.org/10.13039/501100001667 https://doi.org/10.13039/501100002809 https://doi.org/10.13039/501100003329 |
Summary: | This paper proposes a linear parameter varying (LPV) interval unknown input observer for the robust fault diagnosis of actuator faults and ice accretion in unmanned aerial vehicles (UAVs) described by an uncertain model. The proposed interval observer evaluates the set of values for the state, which are compatible with the nominal fault-free and icing-free operation and can be designed in such a way that some information about the nature of the unknown inputs affecting the system can be obtained, thus allowing the diagnosis to be performed. The proposed strategy has several advantages. First, the LPV paradigm allows taking into account operating point variations. Second, the noise rejection properties are enhanced by the presence of the integral term. Third, the interval estimation property guarantees the absence of false alarms. Linear matrix inequality–based conditions for the analysis/design of these observers are provided in order to guarantee the interval estimation of the state and the boundedness of the estimation. The developed theory is supported by simulation results, obtained with the uncertain model of a Zagi Flying Wing UAV, which illustrate the strong appeal of the methodology for identifying correctly unexpected changes in the system dynamics due to actuator faults or icing. EEA Financial Mechanism by a grantfrom Iceland, Liechtenstein, and Norway;Universidad Complutense de Madrid,Grant/Award Number:006-ABEL-IM-2014B; Spanish StateResearch Agency (AEI) and the EuropeanRegional Development Fund (ERFD),Grant/Award Numbers: CICYT DEOCSDPI2016-76493 and CICYT SCAVDPI2017-88403-R; DGR of the Generalitatde Catalunya, Grant/Award Number:2017/SGR/482; Spanish State ResearchAgency through the María de Maeztu Sealof Excellence to IRI, Grant/AwardNumber: MDM-2016-0656; Juan de laCierva Formación, Grant/Award Number:FJCI-2016-29019; Research Council ofNorway through the Centres of Excellencefunding scheme, Grant/Award Number:223254-AMOS; ERCIM Alain BensoussanFellowship programme |
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