A Fault-Tolerant Filter for Systems Subject to Stochastic Faults

Santos, Davi Antônio dos; Yoneyama, Takashi

doi:10.1007/s40313-016-0283-x

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2020

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“…In (Ma et al 2018) a nonlinear high-gain observer has been developed based diagnosis and compensation for actuator and sensor faults in a quadrotor UAV. One popular approach for fault estimation is Kalman Filter (KF) (dos Santos and Yoneyama 2017;Chen et al 2017;Yuan et al 2017;Pourbabaee et al 2015). For nonlinear plants, extended KF (EKF) has been introduced, providing applications in FDI (Bardawily et al 2017;Zhong et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Actuator Faults Estimation for a Helicopter UAV in the Presence of Disturbances

Faraji

Nejati

Abedi

2020

J Control Autom Electr Syst

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The aim of this paper is to develop robust three-stage extended Kalman filter for a model based on a fault detection and identification for nonlinear hover mode system of helicopter unmanned aerial vehicle. In addition, we show that, in considered systems, the actuator faults are affected by each other motivated in five scenarios simulation results. More precisely, the proposed approach estimates and decouples actuator faults in the presence of external disturbances in nonlinear mathematical model. Moreover, we analyze and identify various faults such as bias fault and also catastrophic faults such as stuck and floating faults. Finally, the simulation results show effectiveness of the proposed robust method for detection and isolation of various actuator faults and differentiating bias and stuck faults.

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