Title :
Sensor fault detection algorithm of flight control system under modeling uncertainty and noise disturbance
Author :
Lin Jun ; Zhang Ping
Author_Institution :
Sch. of Autom. Sci. & Electr. Eng., Beihang Univ., Beijing, China
Abstract :
Sensor fault detection method based on UIF (Unknown Input Filter) and minimum variance is proposed to address the real-time fault detection problem of the critical flight sensor and precise positioning the sensor fault in this literature. For aircraft flight control systems that include modeling uncertainties, the UIF method is given and the greatest decoupling between the residuals and the modeling uncertainties is achieved. Through the gain matrix optimizing, the minimum variance estimation error is obtained. The detection function and residual are generated to achieve sensor fault detection and position the fault location. Simulation example of a certain aircraft with system modeling uncertainty and disturbance, the sensor fault detection is verified. For multiple sensor fault, the detection time is determined by senor fault and for only pitot tube fault, the detection time is about 2.5s, in addition, when only angular rate gyro fault, the fault detection is almost one sample time.
Keywords :
aircraft control; aircraft instrumentation; electric sensing devices; error statistics; fault location; filtering theory; matrix algebra; measurement errors; optimisation; reliability; uncertain systems; UIF method; aircraft flight control systems; critical flight sensor; fault location; gain matrix optimization; minimum variance estimation error; pitot tube fault; precise positioning; real-time fault detection problem; sensor fault detection algorithm; system modeling uncertainty; system noise disturbance; unknown input filter; Aircraft; Atmospheric modeling; Electron tubes; Estimation error; Fault detection; Noise; Uncertainty;
Conference_Titel :
Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4799-4700-3
DOI :
10.1109/CGNCC.2014.7007463