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Pré-Publication, Document De Travail Année : 2021

On the informativity of direct identification experiments in dynamical networks

Résumé

Data informativity is a crucial property to ensure the consistency of the prediction error estimate. This property has thus been extensively studied in the open-loop and in the closed-loop cases. In this paper, we consider data informativity in the case of dynamic network identification. In particular, we derive a number of data informativity conditions for the prediction error identification of a particular module of a dynamic network using a direct identification approach. An optimal experiment design approach is also proposed to distinguish between the different situations leading to data informativity.
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Dates et versions

hal-03329586 , version 1 (31-08-2021)
hal-03329586 , version 2 (14-07-2022)

Identifiants

  • HAL Id : hal-03329586 , version 1

Citer

Xavier Bombois, K Colin, P M J van den Hof, H Hjalmarsson. On the informativity of direct identification experiments in dynamical networks. 2021. ⟨hal-03329586v1⟩
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