Actuator Fault Diagnosis in a Boeing 747 Model via Adaptive Modified Two-Stage Kalman Filter | Zendy

Fikret Çalışkan | Zendy; Youmin Zhang | Zendy; N. Eva Wu | Zendy; Jong-Yeob Shin | Zendy

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Actuator Fault Diagnosis in a Boeing 747 Model via Adaptive Modified Two-Stage Kalman Filter

Author(s) -

Fikret Çalışkan,

Youmin Zhang,

N. Eva Wu,

Jong-Yeob Shin

Publication year - 2014

Publication title -

international journal of aerospace engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.361

H-Index - 22

eISSN - 1687-5974

pISSN - 1687-5966

DOI - 10.1155/2014/472395

Subject(s) - control theory (sociology) , actuator , kalman filter , nonlinear system , fault (geology) , fault detection and isolation , engineering , control engineering , computer science , control (management) , artificial intelligence , physics , seismology , geology , quantum mechanics

An adaptive modified two-stage linear Kalman filtering algorithm is utilized to identify the loss of control effectiveness and the magnitude of low degree of stuck faults in a closed-loop nonlinear B747 aircraft. Control effectiveness factors and stuck magnitudes are used to quantify faults entering control systems through actuators. Pseudorandom excitation inputs are used to help distinguish partial loss and stuck faults. The partial loss and stuck faults in the stabilizer are isolated and identified successfully

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