Path-Based Conditions for Local Network Identifiability
(2021) 2021 60th IEEE Conference on Decision and Control (CDC) — Location: Austin, TX, USA (14.December.2021)
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- Abstract
- This work focuses on the generic identifiability of dynamical networks with partial excitation and measurement: a set of nodes are interconnected by transfer functions according to a known topology, some nodes are excited, some are measured, and only a part of the transfer functions are known. Our goal is to determine whether the unknown transfer functions can be generically recovered based on the input-output data collected from the excited and measured nodes.We propose a decoupled version of generic identifiability that is necessary for generic local identifiability and might be equivalent as no counter-example to sufficiency has been found yet in systematic trials. This new notion can be interpreted as the generic identifiability of a larger network, obtained by duplicating the graph, exciting one copy and measuring the other copy. We establish a necessary condition for decoupled identifiability in terms of vertex-disjoint paths in the larger graph, and a sufficient one.
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Citations
Legat, A., & Hendrickx, J. (2021). Path-Based Conditions for Local Network Identifiability. Proceedings of the 60th IEEE Conference on Decision and Control (CDC), 3020-3025. https://doi.org/10.1109/cdc45484.2021.9683062