针对具有传感器故障与加性执行器故障的四旋翼无人机的控制问题，提出一种基于学习观测器的故障弹性容错控制方案。通过处理传感器的故障输出信号,引入新的系统变量，并基于坐标变化构造扩张系统，进而利用传感器故障输出设计学习观测器在线估计系统故障函数与实际输出，进而设计自适应神经网络反步弹性容错控制器实现在无人机同时发生传感器故障与加性执行器故障的情况下，系统实际输出跟踪参考信号，基于Lyapunov稳定性理论证明了闭环系统稳定性。最后，使用四旋翼无人机进行了仿真和户外实验，结果验证了所提方法的有效性。

This paper proposed a learning-observer-based resilient fault-tolerant control scheme for the control problem of quadrotor unmanned aerial vehicles with sensors and actuators faults. By processing the fault output signals of sensors, and based on coordinate changes, an extended system is constructed, and then a learning observer is designed using sensor fault outputs to estimate the system fault function and actual output online. Further, an adaptive neural network backstepping resilient fault-tolerant controller is designed to achieve the actual system output tracking the reference signal in the event of sensor faults and additive actuator faults in the unmanned aerial vehicle. Based on the Lyapunov stability theory, the stability of closed-loop system is proven. Finally, simulations and outdoor experiments are conducted using quadrotor unmanned aerial vehicle and the results validated the effectiveness of the proposed method.