An Improved Distributed Consensus Kalman Filter Design Approach

Event‐triggered consensus Kalman filtering for time‐varying networks and intermittent observations

“…Additionally, assume that each agent activates the event-triggered consensus Kalman filter (22) with the consensus gain (23) and the event-triggered mechanism with event trigger condition (21) over a time-varying communication graph  k . Then the error dynamics (26) are asymptotically stable.…”

“…The omission of the consensus terms from the Kalman gain and error covariance update equation is justified with the assumption that the consensus gain is relatively small. We would like to emphasize that one must be careful while selecting a small consensus gain since this might lead the consensus component in the DCKE to be negligible, as shown in Reference 26. Nevertheless, in Reference 25 it was shown that (4) has stable estimator dynamics.…”

“…In the previous subsection we proposed a centralized solution for the determination of the consensus factor $$$ {\gamma}_k $$$ that required global network information, that is, the largest eigenvalue of the Laplacian matrix $$$ L $$$ and the augmented matrix $$$ {Y}_k $$$. In our previous work, 26 we showed that this choice of gain can be problematic for time‐varying communication networks. Additionally, for large‐scale networks, the centralized architecture may also require heavy computational tools.…”