Robust Reduced Order Thau Observer With the Adaptive Fault Estimator for the Unmanned Air Vehicles

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dc.authoridTutsoy, Onder/0000-0001-6385-3025
dc.authoridAhmadi, Karim/0000-0002-2633-3351
dc.authoridNabavi Chashmi, Seyed Yaser/0000-0003-1836-2600
dc.authoridasadi, davood/0000-0002-2066-6016
dc.contributor.authorTutsoy, Önder
dc.contributor.authorAsadi, Davood
dc.contributor.authorAhmadi, Karim
dc.contributor.authorNabavi-Chashmi, Seyed-Yaser
dc.date.accessioned2025-01-06T17:43:49Z
dc.date.available2025-01-06T17:43:49Z
dc.date.issued2023
dc.description.abstractDeveloping fault detection and diagnoses algorithms for the unmanned air vehicles such as the quadrotors is challenging since they are intrinsically non-linear, time-varying, unstable, and uncertain. This paper develops a reduced order Thau observer by only considering the uncertain rotational dynamics, which are re-constructed as the dominant linear and non-linear for the design purpose. Therefore, the proposed Thau observer is just third order and can reveal a rotational state estimation error in the presence of the quadrotor faults. This paper also equips the proposed Thau observer with a simple online adaptive fault estimation law, which is able to recognize up to two faulty actuators instantly using the estimated rotational state error. Lyapunov analysis confirms the error convergence in both the Thau observer states and the adaptive fault estimates. In addition, this paper constructs a batch type least-squares projection approach to quantify the magnitude percentages of the actuator failures. Moreover, to show the feasibility of the proposed algorithm, this paper extensively analyses the fault detection and diagnosis results performed in the simulation and real-time environments. Finally, to demonstrate the superiority of the proposed algorithm, it is compared with a recent Kalman filter based quadrotor fault estimation research under the equal conditions.
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUEBITAK) [120M793]
dc.description.sponsorshipThis work was supported by the Scientific and Technological Research Council of Turkey (TUEBITAK) through 3501 program, under Grant 120M793. The review of this article was coordinated by Prof. Shima Nazari.
dc.identifier.doi10.1109/TVT.2022.3214479
dc.identifier.endpage1610
dc.identifier.issn0018-9545
dc.identifier.issn1939-9359
dc.identifier.issue2
dc.identifier.scopus2-s2.0-85148427280
dc.identifier.scopusqualityQ1
dc.identifier.startpage1601
dc.identifier.urihttps://doi.org/10.1109/TVT.2022.3214479
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2815
dc.identifier.volume72
dc.identifier.wosWOS:000944202400017
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIEEE-Inst Electrical Electronics Engineers Inc
dc.relation.ispartofIeee Transactions on Vehicular Technology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectObservers
dc.subjectQuadrotors
dc.subjectVehicle dynamics
dc.subjectActuators
dc.subjectHeuristic algorithms
dc.subjectFault detection
dc.subjectDynamics
dc.subjectfault diagnoses
dc.subjectquadrotors
dc.subjectthau observer
dc.subjectunmanned air vehicles
dc.titleRobust Reduced Order Thau Observer With the Adaptive Fault Estimator for the Unmanned Air Vehicles
dc.typeArticle

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