Data Informativity for the Identification of MISO FIR Systems with Filtered White Noise Excitation - Université Claude Bernard Lyon 1 Accéder directement au contenu
Communication Dans Un Congrès Année : 2019

Data Informativity for the Identification of MISO FIR Systems with Filtered White Noise Excitation

Résumé

For Prediction Error Identication, there are two main ingredients to get a consistent estimate: one of them is the data informativity with respect to (w.r.t.) the considered model structure. One common criterion used for the informativity is the positive deniteness of the input density spectral power (DSP) matrix at all frequencies. This criterion is not appropriate for multisine excitation but can be used for ltered white noise excitation for many identication problems. However, this criterion is not necessary and its application for some identication problems might not be possible. In this paper, we propose a necessary and sucient condition for the data informativity in the case of multiple-inputs single-output (MISO) nite impulse response (FIR) model structure in open-loop.
Fichier principal
Vignette du fichier
CDC_paper_version_hal.pdf (441.4 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02161598 , version 1 (20-06-2019)

Identifiants

Citer

Kévin Colin, Xavier Bombois, Laurent Bako, Federico Morelli. Data Informativity for the Identification of MISO FIR Systems with Filtered White Noise Excitation. 2019 58th Conference on Decision and Control (CDC), Dec 2019, Nice, France. ⟨10.1109/CDC40024.2019.9029300⟩. ⟨hal-02161598⟩
118 Consultations
126 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More