Actuator and sensor fault detection and diagnosis of quadrotor based on Two-Stage Kalman Filter

This paper addresses the problem of sensor and actuator fault detection and diagnosis (FDD) of an unmanned quadrotor helicopter in the presence of the observation and process noises. To this end a Two-Stage Kalman Filter (TSKF) to detect, isolate and identify faults is used. Sensor faults are assumed to be bias faults and actuator faults are modeled as a loss of effectiveness in the propellers. Also a discrete-time Linear Quadratic Regulator (LQR) controller is used to make the system response to follow a desired trajectory.