Distributed Dissipative Filtering with Consensus on Estimation: A Two-Dimensional System Method

This paper deals with the problem of distributed estimation with consensus by utilizing a two-dimensional (2-D) system approach. The consensus protocol is employed as the information fusion strategy, enabling local communication among neighboring nodes to drive their estimates toward consensus, and the distributed dissipative filter is designed on each node. It is shown that the estimation error dynamics is asymptotically stable and meets the prescribed dissipativity performance. Moreover, by incorporating consensus updates in an additional time dimension, the estimator parameters are determined through a constructed 2-D system approach, thereby reducing the design complexity. Simulations demonstrate the validity of the proposed algorithm.