基于改进自适应卡尔曼滤波的容错控制

Improved Adaptive Kalman Filter-based Fault-tolerant Control

  • 摘要: 针对离散系统的执行器和传感器故障以及存在的白噪声干扰,提出了一种基于改进自适应卡尔曼滤波和动态输出反馈的容错控制方法.在白噪声干扰下,该方法利用改进的自适应卡尔曼滤波对系统执行器和传感器故障进行同步估计,同时利用李亚普诺夫函数分析了改进自适应卡尔曼滤波的收敛性;对于系统状态不完全可测的问题,根据得到的故障信息,基于动态输出反馈和圆盘稳定定理设计容错控制器,使系统响应恢复到正常状态.最后利用飞行控制系统模型对提出的方法进行了验证,仿真表明该方法不仅能对执行器和传感器故障进行同步估计,而且在故障情况下能够对系统响应进行修正,具有良好的容错控制能力.

     

    Abstract: A fault-tolerant control method based on an improved adaptive Kalman filter and dynamic output feedback is proposed for discrete systems of actuator and sensor faults along with white noise. Under the noise interference, the faults of the system actuator and sensor are simultaneously estimated by the improved adaptive Kalman filter, whose convergence is analyzed by the Lyapunov function. According to the obtained information of faults, the fault-tolerant controller based on the dynamic output feedback and disk stability theorem is designed for the problem that the system state is not fully measurable to make the system response return to the normal state. Finally, the method is validated by the flight control system model. The results show that the method can not only simultaneously estimate faults of the actuator and sensor but can also correct the system response under faults, indicating that the control method has good fault tolerance.

     

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