Active Fault-Tolerant Control for Quadrotor UAV against Sensor Fault Diagnosed by the Auto Sequential Random Forest

Abstract

Active disturbance rejection control (ADRC) is a model-independent method widely used in passive fault-tolerant control of the quadrotor unmanned aerial vehicle. While ADRC’s effectiveness in actuator fault treatment has been proven, its tolerance to sensor faults requires improvements. In this paper, an ADRC-based active fault-tolerant control (AFTC) scheme is proposed to control the flying attitude against sensor fault for reliability enhancement. Specifically, a semi-model-dependent state tracker is raised to reduce the influence of slow tracking, and accentuate the sensor fault even in varying maneuvers. Derived from the random forest, an enhanced method named auto sequential random forest is designed and applied to isolate and identify faults in real time. Once the tolerance compensation is generated with the fault information, a high-performance AFTC is achieved. The simulation results show that the proposed method can effectively follow the residual when a sensor fault and a change of maneuver occur concurrently. Precise fault information is obtained within 0.04 s, even for small faults on the noise level. The diagnosis accuracy is greater than 86.05% (100% when small faults are excluded), and the identification precision exceeds 97.25%. The short settling time (0.176 s when the small fault is excluded) and modest steady-state error validate the advanced and robust tolerance performance of the proposed AFTC method.