中国科学院自动化研究所机构知识库

Fault detection and isolation (FDI) plays an important role in guaranteeing system
safety and reliability for unmanned aerial vehicles (UAVs). This paper focuses on developing
a method for detecting UAV sensor faults by using existing sensors, such as pitot tube, gyro,
accelerometer and wind angle sensor. We formulate the kinematics as a nonlinear state space
system, which requires no dynamic information and thus is applicable to all aircraft. To illustrate
the method, we investigate five fault-detection scenarios, namely, faulty pitot tube, angle-ofattack
sensor, sideslip sensor, accelerometer and gyro, and design a FDI structure including
five faulty sensors. Then, considering the unknown disturbance, the proportional and multiple
integral (PMI) fault detection filter (FDF) is proposed for the state and input estimation. A
structure including two residuals are employed to detect and isolate the faults of the proposed
faulty sensors. Finally, the performance of the proposed methodology is evaluated through flight
experiments of the UAV.