Print Email Facebook Twitter Single module identifiability in linear dynamic networks with partial excitation and measurement Title Single module identifiability in linear dynamic networks with partial excitation and measurement Author Shi, S. (TU Delft Team Bart De Schutter; Eindhoven University of Technology) Cheng, Xiaodong (University of Cambridge) Van den Hof, Paul M.J. (Eindhoven University of Technology) Date 2023 Abstract Identifiability of a single module in a network of transfer functions is determined by whether a particular transfer function in the network can be uniquely distinguished within a network model set, on the basis of data. Whereas previous research has focused on the situations that all network signals are either excited or measured, we develop generalized analysis results for the situation of partial measurement and partial excitation. As identifiability conditions typically require a sufficient number of external excitation signals, this article introduces a novel network model structure such that excitation from unmeasured noise signals is included, which leads to less conservative identifiability conditions than relying on measured excitation signals only. More importantly, graphical conditions are developed to verify global and generic identifiability of a single module based on the topology of the dynamic network. Depending on whether the input or the output of the module can be measured, we present four identifiability conditions which cover all possible situations in single module identification. These conditions further lead to synthesis approaches for allocating excitation signals and selecting measured signals, to warrant single module identifiability. In addition, if the identifiability conditions are satisfied for a sufficient number of external excitation signals only, indirect identification methods are developed to provide a consistent estimate of the module. All the obtained results are also extended to identifiability of multiple modules in the network. Subject Brain modelingData modelsdynamic networksgraph theoryidentifiabilityMISO communicationNetwork topologyPower system dynamicsSystem identificationTopologyTransfer functions To reference this document use: http://resolver.tudelft.nl/uuid:8561dfab-02f8-4e01-947e-7d8014922c9b DOI https://doi.org/10.1109/TAC.2021.3137787 Embargo date 2023-07-01 ISSN 0018-9286 Source IEEE Transactions on Automatic Control, 68 (1), 285-300 Bibliographical note Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type journal article Rights © 2023 S. Shi, Xiaodong Cheng, Paul M.J. Van den Hof Files PDF Single_Module_Identifiabi ... rement.pdf 1.35 MB Close viewer /islandora/object/uuid:8561dfab-02f8-4e01-947e-7d8014922c9b/datastream/OBJ/view