Structural and Strongly Structural Input and State Observability of Linear Network Systems

Sebin Gracy 1 Federica Garin 1 Alain Kibangou 1
1 NECS - Networked Controlled Systems
Inria Grenoble - Rhône-Alpes, GIPSA-DA - Département Automatique
Abstract : This paper studies linear network systems affected by multiple unknown inputs with the objective of reconstructing both the initial state and the unknown input with one time-step delay. We state conditions under which both the whole network state and the unknown input can be reconstructed from output measurements, over every window of length N , N being the dimension of the system, for all system matrices that share a common zero/non-zero pattern (uniform N-step strongly structural input and state observability) or at least for almost all system matrices that share a common zero/non-zero pattern (uniform N-step structural input and state observability). Based on some specific assumptions on the structure of the interactions between the unknown input and the network states, we show that such a characterization depends only on strongly structural (resp. structural) observability properties of a suitable subsystem.
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Sebin Gracy, Federica Garin, Alain Kibangou. Structural and Strongly Structural Input and State Observability of Linear Network Systems. IEEE Transactions on Control of Network Systems, IEEE, 2018, 5 (4), pp.2062-2072. ⟨10.1109/TCNS.2017.2782489⟩. ⟨hal-01663175⟩

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