Sensor and actuator FDI applied to an UAV dynamic model

In this paper, an approach to isolate the sensor and control surface/actuator failures affecting the innovation of Kalman filter was proposed and applied to an UAV dynamic model. To diagnose if the fault is a sensor fault or an actuator fault, a two-stage Kalman filter (TSKF) insensitive to actuator faults is developed. In the proposed method, sensor faults are isolated by the normalized innovation of Kalman filter. Furthermore, an adaptive linear adaptive TSKF algorithm is used to estimate the loss of control effectiveness and the magnitude of degree of stuck faults in a UAV model. Control effectiveness factors and stuck magnitudes are used to quantify faults entering control systems through actuators. In the simulations, the longitudinal and lateral dynamics of the UAV model is considered, and detection and isolation of sensor and control surface/actuator failures are examined.