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基于平方根容积卡尔曼滤波方法(Square root cubature Kalman filter,SCKF),研究一类非线性随机动态系统的故障检测与估计问题。SCKF对解决复杂非线性系统的状态估计问题,具有精度高、稳定性优和计算复杂度低等优点。针对发生执行器故障的非线性随机动态系统,采用SCKF估计系统状态,并根据状态估计结果,利用滑动时间窗口技术设计残差信号,检测故障发生。在检测到故障之后,构造增广系统,实现对执行器故障幅值的估计。通过仿真试验验证了所提出方法的有效性。
Based on Square root cubature Kalman filter (SCKF), the problem of fault detection and estimation for a class of nonlinear stochastic dynamic systems is studied. SCKF has the advantages of high precision, good stability and low computational complexity for solving the state estimation of complex nonlinear systems. Aiming at the nonlinear stochastic dynamic system with actuator failure, the state of the system is estimated by using SCKF. According to the state estimation results, the residual signal is designed by sliding time window to detect the fault. After the fault is detected, an augmentation system is constructed to estimate the actuator fault amplitude. The simulation results show the effectiveness of the proposed method.