基于多故障分类的Hex-Rotor无人飞行器的执行单元故障检测与自重构

为了实现对Hex-Rotor无人飞行器执行单元故障的快速准确检测，提高飞行器的安全性和可靠性，提出基于多故障分类的执行单元故障检测与自重构算法.在对执行单元故障进行分类的基础上，建立执行单元升力故障模型，构建基于扩展卡尔曼滤波算法的故障观测器组，实现故障的检测与隔离.利用故障观测器的输出信号，对不同故障进行相应的自重构，设计基于多故障分类的自重构控制算法.通过理论分析、数值仿真和实际飞行，验证了提出算法的有效性.结果表明，利用该算法能够快速、准确地完成故障检测与隔离，在故障条件下保证飞行器姿态控制的稳定性.

Faults detection and self-reconfiguration for execution units of Hex-Rotor unmanned aerial vehicle based on multiple fault classification

The safety and reliability of the Hex-Rotor UAV were improved in order to detect the fault of the execution units of Hex-Rotor unmanned aerial vehicle (UAV) quickly and accurately. The faults detection and self-reconfiguration for execution units of Hex-Rotor UAV was proposed based on multiple fault classification. The lift model of the execution units was established based on the classification of the fault of the execution units. The fault observer group based on the extended Kalman filter (EKF) algorithm was constructed to achieve fault detection and isolation. Then a self-reconfigurable control algorithm based on multiple fault classification was designed by using the output signal of the fault observer group. The effectiveness of the proposed algorithm was verified by theoretical analysis, numerical simulation and actual flight. Results show that the algorithm can complete fault detection and isolation quickly and accurately, and ensure the stability of the attitude control of the Hex-Rotor UAV under fault condition.