复杂网络的事件驱动故障估计

Event-triggered Fault Estimation for Complex Networks

  • 摘要: 针对一类非线性耦合的复杂网络系统,提出了一种基于复杂网络估计器的近似最优故障估计方法.首先将复杂网络的状态与故障进行增广,然后对增广后的状态和故障进行了联合状态估计.为了处理多信号传输可能发生的数据冲突,采用了事件驱动的方法使复杂网络的输出传输至远程估计器.通过递推矩阵方程方法给出了估计误差协方差矩阵的上界,并通过设计估计器参数使得该上界在迹的意义下最小.最后,通过仿真例子验证了所提联合估计方案的可行性和有效性.

     

    Abstract: We propose an approximate optimal fault estimation method based on complex network system estimator for a class of nonlinear systems with strong couplings. First, we jointly estimate the state and fault of the complex network via the augment method, and then perform the joint state estimation on the augmented state and fault. To address the data collision that may occur in multi-signal transmission, we transmit the output of the complex network to the remote estimator using an event-triggered approach. The parameters of the estimator are obtained by solving several recursive matrix equations such that an upper bound of the estimation error covariance is established and minimized. Finally, we present a simulation example to verify the feasibility of the proposed state estimation scheme.

     

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