Adaptive Filtering Against Sensor/Actuator Faults

A new fault tolerant estimation method of unmanned aerial vehicle (UAV) dynamics in the presence of sensor/actuator faults with both adaptivity and robustness is proposed. Choosing between robust and adaptive approaches in the event of a sensor/actuator fault is the topic of this study. We describe two methods: a robust technique with R-adaptation and an adaptive method with Q-adaptation. Fault detection in the Kalman filter is based on the chi-square distribution of the normalized quadratic innovation function (NQI). After detection of fault it is proposed to run simultaneously both, R-adaptive and Q-adaptive Kalman filters and compare their estimation performances to distinguish the sensor and actuator faults. As a performance criterion the mean of the quadratic differences between estimation and extrapolation values of robust and adaptive filters is proposed to use.