Exploiting unmeasured disturbance signals in identifiability of linear dynamic networks with partial measurement and partial excitation

Shengling Shi; Xiaodong Cheng; Paul M.J. Van den Hof

Exploiting unmeasured disturbance signals in identifiability of linear dynamic networks with partial measurement and partial excitation

Shengling Shi
, Xiaodong Cheng
, Paul M.J. Van den Hof

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

Identifiability conditions for networks of transfer functions require a sucient
number of external excitation signals, which are typically measured reference signals. In this abstract, we introduce an equivalent network model structure to address the contribution of unmeasured noises to identifiability analysis in the setting with partial excitation and partial measurement. With this model structure, unmeasured disturbance signals can be exploited as excitation sources, which leads to less conservative identifiability conditions.

Original language	English
Title of host publication	Preprints, 19th IFAC Symposium on System Identification
Pages	264-267
Number of pages	4
Publication status	Published - 13 Jul 2021
Event	19th IFAC Symposium on System Identification (SYSID 2021) - Virtual, Padova, Italy Duration: 13 Jul 2021 → 16 Jul 2021 Conference number: 19 https://www.sysid2021.org/

Conference

Conference	19th IFAC Symposium on System Identification (SYSID 2021)
Abbreviated title	SYSID 2021
Country/Territory	Italy
City	Padova
Period	13/07/21 → 16/07/21
Internet address	https://www.sysid2021.org/

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@inproceedings{cac305a3cb144112bdb49c9d8e874453,

title = "Exploiting unmeasured disturbance signals in identifiability of linear dynamic networks with partial measurement and partial excitation",

abstract = "Identifiability conditions for networks of transfer functions require a sucient number of external excitation signals, which are typically measured reference signals. In this abstract, we introduce an equivalent network model structure to address the contribution of unmeasured noises to identifiability analysis in the setting with partial excitation and partial measurement. With this model structure, unmeasured disturbance signals can be exploited as excitation sources, which leads to less conservative identifiability conditions.",

author = "Shengling Shi and Xiaodong Cheng and \{Van den Hof\}, \{Paul M.J.\}",

year = "2021",

month = jul,

day = "13",

language = "English",

pages = "264--267",

booktitle = "Preprints, 19th IFAC Symposium on System Identification",

note = "19th IFAC Symposium on System Identification (SYSID 2021), SYSID 2021 ; Conference date: 13-07-2021 Through 16-07-2021",

url = "https://www.sysid2021.org/",

}

Shi, S, Cheng, X & Van den Hof, PMJ 2021, Exploiting unmeasured disturbance signals in identifiability of linear dynamic networks with partial measurement and partial excitation. in Preprints, 19th IFAC Symposium on System Identification. pp. 264-267, 19th IFAC Symposium on System Identification (SYSID 2021), Padova, Italy, 13/07/21. <http://publications.pvandenhof.nl/Paperfiles/Shi&etal_SYSID2021.pdf>

Exploiting unmeasured disturbance signals in identifiability of linear dynamic networks with partial measurement and partial excitation. / Shi, Shengling; Cheng, Xiaodong; Van den Hof, Paul M.J.
Preprints, 19th IFAC Symposium on System Identification. 2021. p. 264-267.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Exploiting unmeasured disturbance signals in identifiability of linear dynamic networks with partial measurement and partial excitation

AU - Shi, Shengling

AU - Cheng, Xiaodong

AU - Van den Hof, Paul M.J.

N1 - Conference code: 19

PY - 2021/7/13

Y1 - 2021/7/13

N2 - Identifiability conditions for networks of transfer functions require a sucient number of external excitation signals, which are typically measured reference signals. In this abstract, we introduce an equivalent network model structure to address the contribution of unmeasured noises to identifiability analysis in the setting with partial excitation and partial measurement. With this model structure, unmeasured disturbance signals can be exploited as excitation sources, which leads to less conservative identifiability conditions.

AB - Identifiability conditions for networks of transfer functions require a sucient number of external excitation signals, which are typically measured reference signals. In this abstract, we introduce an equivalent network model structure to address the contribution of unmeasured noises to identifiability analysis in the setting with partial excitation and partial measurement. With this model structure, unmeasured disturbance signals can be exploited as excitation sources, which leads to less conservative identifiability conditions.

M3 - Conference contribution

SP - 264

EP - 267

BT - Preprints, 19th IFAC Symposium on System Identification

T2 - 19th IFAC Symposium on System Identification (SYSID 2021)

Y2 - 13 July 2021 through 16 July 2021

ER -

Exploiting unmeasured disturbance signals in identifiability of linear dynamic networks with partial measurement and partial excitation

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