Quadrotor Unmanned Aerial Vehicles (UAVs) have attracted significant attention in recent years due to their potentials in various military and commercial applications. Four propellers mounted on the shafts of four brushless DC motors generate the required thrust and torques needed for altitude and attitude control of quadrotors. However, structural damage to the propellers and rotor degradation can lead to actuator faults in the form of a partial loss of effectiveness in a rotor, which may result in degraded tracking performance or even loss of stability of the control system. This paper presents the systematic design, analysis, and real-time experimental results of a fault detection and isolation algorithm for quadrotor actuator faults using nonlinear adaptive estimation techniques. The fault diagnosis architecture consists of a nonlinear fault detection estimator and a bank of nonlinear adaptive fault isolation estimators designed based on the functional structures of the faults under consideration. Adaptive
thresholds for fault detection and isolation are systematically designed to enhance the robustness and fault sensitivity of the diagnostic algorithm. Using an indoor quadrotor test environment, real-time experimental flight test results are shown to illustrate the effectiveness of the algorithms.
How to Cite
fault isolation, Actuator Fault Diagnosis, Fault Estimation, Quadrotor UAVs
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