Abstract: We study the decentralized resilient state-tracking problem in which each node in a network has the objective of tracking the state of a linear dynamical system based on its local measurements and information exchanged with its neighboring nodes, despite an attack on some of the nodes. We propose a novel algorithm that solves the decentralized resilient state-tracking problem by relating it to the dynamic average consensus problem. Compared with existing solutions in the literature, our algorithm provides a solution for the most general class of decentralized resilient state-tracking problem instances.
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