Single module identifiability in linear dynamic networks

Harm Weerts; Paul M.J. Van den Hof; Arne Dankers

doi:10.1109/CDC.2018.8619365

Single module identifiability in linear dynamic networks

Harm Weerts, Paul M.J. Van den Hof, Arne Dankers

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

18 Citations (Scopus)

88 Downloads (Pure)

Abstract

A recent development in data-driven modeling addresses the problem of identifying dynamic models of interconnected systems, represented as linear dynamic networks. For these networks the notion of network identifiability has been introduced recently, which reflects the property that different network models can be distinguished from each other. Network identifiability is extended to cover the uniqueness of a single module in the network model, and conditions for single module identifiability are derived and formulated in terms of path-based topological properties of the network models.

Original language	English
Title of host publication	2018 IEEE Conference on Decision and Control, CDC 2018
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	4725-4730
Number of pages	6
ISBN (Electronic)	9781538613955
DOIs	https://doi.org/10.1109/CDC.2018.8619365
Publication status	Published - 18 Jan 2019
Event	57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States Duration: 17 Dec 2018 → 19 Dec 2018 Conference number: 57

Conference

Conference	57th IEEE Conference on Decision and Control, CDC 2018
Abbreviated title	CDC 2018
Country/Territory	United States
City	Miami
Period	17/12/18 → 19/12/18

Funding

This project has received funding from the European Research Council (ERC), Advanced Research Grant SYSDYNET, under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 694504).

Access to Document

10.1109/CDC.2018.8619365

Weerts&etal_CDC2018_finalFinal author version , 213 KB

Cite this

@inproceedings{d4101f2ae9ad4b3ab509d045266f4586,

title = "Single module identifiability in linear dynamic networks",

abstract = "A recent development in data-driven modeling addresses the problem of identifying dynamic models of interconnected systems, represented as linear dynamic networks. For these networks the notion of network identifiability has been introduced recently, which reflects the property that different network models can be distinguished from each other. Network identifiability is extended to cover the uniqueness of a single module in the network model, and conditions for single module identifiability are derived and formulated in terms of path-based topological properties of the network models.",

author = "Harm Weerts and {Van den Hof}, {Paul M.J.} and Arne Dankers",

year = "2019",

month = jan,

day = "18",

doi = "10.1109/CDC.2018.8619365",

language = "English",

pages = "4725--4730",

booktitle = "2018 IEEE Conference on Decision and Control, CDC 2018",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "57th IEEE Conference on Decision and Control, CDC 2018, CDC 2018 ; Conference date: 17-12-2018 Through 19-12-2018",

}

Weerts, H, Van den Hof, PMJ & Dankers, A 2019, Single module identifiability in linear dynamic networks. in 2018 IEEE Conference on Decision and Control, CDC 2018., 8619365, Institute of Electrical and Electronics Engineers, Piscataway, pp. 4725-4730, 57th IEEE Conference on Decision and Control, CDC 2018, Miami, Florida, United States, 17/12/18. https://doi.org/10.1109/CDC.2018.8619365

Single module identifiability in linear dynamic networks. / Weerts, Harm; Van den Hof, Paul M.J.; Dankers, Arne.
2018 IEEE Conference on Decision and Control, CDC 2018. Piscataway: Institute of Electrical and Electronics Engineers, 2019. p. 4725-4730 8619365.

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

TY - GEN

T1 - Single module identifiability in linear dynamic networks

AU - Weerts, Harm

AU - Van den Hof, Paul M.J.

AU - Dankers, Arne

N1 - Conference code: 57

PY - 2019/1/18

Y1 - 2019/1/18

N2 - A recent development in data-driven modeling addresses the problem of identifying dynamic models of interconnected systems, represented as linear dynamic networks. For these networks the notion of network identifiability has been introduced recently, which reflects the property that different network models can be distinguished from each other. Network identifiability is extended to cover the uniqueness of a single module in the network model, and conditions for single module identifiability are derived and formulated in terms of path-based topological properties of the network models.

AB - A recent development in data-driven modeling addresses the problem of identifying dynamic models of interconnected systems, represented as linear dynamic networks. For these networks the notion of network identifiability has been introduced recently, which reflects the property that different network models can be distinguished from each other. Network identifiability is extended to cover the uniqueness of a single module in the network model, and conditions for single module identifiability are derived and formulated in terms of path-based topological properties of the network models.

UR - http://www.scopus.com/inward/record.url?scp=85062171733&partnerID=8YFLogxK

U2 - 10.1109/CDC.2018.8619365

DO - 10.1109/CDC.2018.8619365

M3 - Conference contribution

AN - SCOPUS:85062171733

SP - 4725

EP - 4730

BT - 2018 IEEE Conference on Decision and Control, CDC 2018

PB - Institute of Electrical and Electronics Engineers

CY - Piscataway

T2 - 57th IEEE Conference on Decision and Control, CDC 2018

Y2 - 17 December 2018 through 19 December 2018

ER -

Single module identifiability in linear dynamic networks

Abstract

Conference

Funding

Access to Document

Other files and links

Fingerprint

Cite this