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This paper deals with a distributed state estimation problem for jointlyobservable multi-agent systems operated over various time-varying networktopologies. The results apply when the system matrix of the system to beobserved contains eigenvalues with positive real parts. They also can apply tosituations where the communication networks are disconnected at every instant.We present sufficient conditions for the existence of distributed observers forgeneral linear systems over periodic communication networks. Using an averagingapproach, it is shown that the proposed distributed observer can provideexponentially converging state estimates of the state of the linear system whenthe network is uniformly connected on average. This average connectednesscondition offers a more relaxed assumption that includes periodic switching,Markovian switching and Cox process switching as special cases. All the agentsin the network share the estimated state with their neighbours through thenetwork and cooperatively reconstruct the entire state locally. Furthermore,this study presents two exponential stability results for two classes ofswitched systems, providing valuable tools in related distributed stateestimation approaches. A toy example and three practical applications areprovided to illustrate the effectiveness of the theoretical results.

Distributed State Estimation for Jointly Observable Linear Systems over Time-varying Networks