AESMF Based Sensor Fault diagnosis for RUAVs
An Adaptive Extended Set-Member Filter (AESMF) with the adaptive selection scheme of the filter parameters is incorporated with the nonlinear attitude state estimation equation to build a sensor fault diagnosis system which can provide guaranteed sensor fault detection. Compared with other sensor fault diagnosis systems based on Kalman Filter (KF) or other probability based methods which can just provide a fault probability distribution but not tell the exact result, in this paper, with the advantage of ellipsoid bound of set-member, we try to implement AESMF to tackle this problem and provide the exact fault diagnosis result. The AESMF is incorporated into the navigation system equation and the sensor fault diagnosis method is introduced. Simulations are conducted and the algorithm is compared with the EKF based navigation system, the result demonstrates the improvement of this method.
AESMF Sensor fault diagnosis RUAV
Chong Wu Juntong Qi Jianda Han
The Graduate School of the Chinese Academy of Sciences, Beijing 100080 State Key Laboratory of Robot State Key Laboratory of Robotics, Shenyang Institute and Automation, Chinese Academy of Sciences, Sh
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
3396-3401
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）