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How to realize high-level autonomy of individuals is one of key technicalissues to promote swarm intelligence of multi-agent (node) systems withcollective tasks, while the fully distributed design is a potential way toachieve this goal. This paper works on the fully distributed state estimationand cooperative stabilization problem of linear time-invariant (LTI) plantswith multiple nodes communicating over general directed graphs, and is aimed toprovide a fully distributed framework for each node to perform cooperativestabilization tasks. First, by incorporating a novel adaptive law, aconsensus-based estimator is designed for each node to obtain the plant statebased on its local measurement and local interaction with neighbors, withoutusing any global information of the communication topology. Subsequently, alocal controller is developed for each node to stabilize the plantcollaboratively with performance guaranteed under mild conditions.Specifically, the proposed method only requires that the communication graph bestrongly connected, and the plant be collectively controllable and observable.Further, the proposed method can be applied to pure fully distributed stateestimation scenarios and modified for noise-bounded LTI plants. Finally, twonumerical examples are provided to show the effectiveness of the theoreticalresults.

A Framework on Fully Distributed State Estimation and Cooperative Stabilization of LTI Plants