Signal selection for local module identification in linear dynamic networks: A graphical approach

Shengling Shi, Xiaodong Cheng (Corresponding author), Bart De Schutter, Paul M.J. Van den Hof

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In a dynamic network of interconnected transfer functions, it is not necessary to use all the node signals for estimating a local transfer function. Given the network topology, detailed conditions are available for selecting inputs and outputs in a (MIMO) predictor model that warrants consistent and minimum variance estimation of a target module through the so-called local direct method. Motivated by the existing minimum-input signal selection approach that gradually incorporates additional signals, an alternative graphical algorithm for signal selection is developed in this work by directly exploiting the complete network graph. Then, as a straightforward application of existing analytical results, graphical conditions for consistent identification are derived for the novel signal selection approach. We show by an example that in some cases, for the consistent estimation of the target module, the developed method leads to fewer selected signals than the original minimum-input method.

Originele taal-2Engels
Pagina's (van-tot)2407-2412
Aantal pagina's6
Nummer van het tijdschrift2
StatusGepubliceerd - nov. 2023
Evenement22nd World Congress of the International Federation of Automatic Control (IFAC 2023 World Congress) - Yokohama, Japan
Duur: 9 jul. 202314 jul. 2023
Congresnummer: 22

Bibliografische nota

Publisher Copyright:
Copyright © 2023 The Authors. This is an open access article under the CC BY-NC-ND license (


Horizon 2020 Framework Programme
European Research Councilao2021


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