Abstract
We consider the identification of networks of linear time-invariant dynamical systems whose node signals are measured and are connected by causal linear time-invariant transfer functions. The external signals at the nodes may comprise both known excitation signals and unknown stationary noise signals. The identification of such networks comprise two essentially different problems. The first is to find conditions on the external excitation signals that allow the identification of the whole network from the measured node signals and excitation signals. The second problem is the identification of a particular module (i.e., transfer function) embedded in the network. We present state of the art results for both problems.
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Acknowledgements
This work is supported by the Program Science Without Borders, CNPq—Conselho Nacional de Desenvolvimento Científico e Tecnológico, Brazil, and by the Belgian Program on Interuniversity Attraction Poles, initiated by the Belgian Federal Science Policy Office.
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Gevers, M., Bazanella, A.S., Pimentel, G.A. (2018). Identification of Dynamical Networks. In: Tempo, R., Yurkovich, S., Misra, P. (eds) Emerging Applications of Control and Systems Theory. Lecture Notes in Control and Information Sciences - Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-67068-3_11
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DOI: https://doi.org/10.1007/978-3-319-67068-3_11
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