A Factor Graph Approach to Parameter Identification for Affine LPV Systems

C. Hoffmann; A. Isler; P. Rostalski

doi:10.23919/ACC.2017.7963231

A Factor Graph Approach to Parameter Identification for Affine LPV Systems

C. Hoffmann, A. Isler, P. Rostalski

Institut für Medizinische Elektrotechnik

ABB Switzerland Ltd

Abstract

Factor graphs are a versatile graphical representation of factorizable functions. As a probabilistic graphical model they allow to visualize conditional independence, which can be exploited for efficiently solving inference problems by means of message passing along the nodes of the graph. In this paper, a novel factor graph formulation of the expectation maximization-based estimation technique for affine linear parameter-varying system identification is presented. Furthermore, a recursive reformulation of the algorithm suitable for tracking time-varying changes both accounted and unaccounted for by a pre-defined linear parameter-varying system description is immediate from its factor graph-based formulation.

Originalsprache	Englisch
Titel	2017 American Control Conference (ACC)
Seitenumfang	6
Herausgeber (Verlag)	IEEE
Erscheinungsdatum	29.06.2017
Seiten	1910-1915
Aufsatznummer	7963231
ISBN (Print)	978-1-5090-5994-2, 978-1-5090-4583-9
ISBN (elektronisch)	978-1-5090-5992-8
DOIs	https://doi.org/10.23919/ACC.2017.7963231
Publikationsstatus	Veröffentlicht - 29.06.2017
Veranstaltung	2017 American Control Conference - Sheraton Seattle Hotel , Seattle, USA / Vereinigte Staaten Dauer: 24.05.2017 → 26.05.2017 Konferenznummer: 128855

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10.23919/ACC.2017.7963231

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@inproceedings{c187b3f3c7b24d7faf2df09721adc6e8,

title = "A Factor Graph Approach to Parameter Identification for Affine LPV Systems",

abstract = "Factor graphs are a versatile graphical representation of factorizable functions. As a probabilistic graphical model they allow to visualize conditional independence, which can be exploited for efficiently solving inference problems by means of message passing along the nodes of the graph. In this paper, a novel factor graph formulation of the expectation maximization-based estimation technique for affine linear parameter-varying system identification is presented. Furthermore, a recursive reformulation of the algorithm suitable for tracking time-varying changes both accounted and unaccounted for by a pre-defined linear parameter-varying system description is immediate from its factor graph-based formulation.",

author = "C. Hoffmann and A. Isler and P. Rostalski",

year = "2017",

month = jun,

day = "29",

doi = "10.23919/ACC.2017.7963231",

language = "English",

isbn = "978-1-5090-5994-2",

series = "Proceedings of the American Control Conference",

publisher = "IEEE",

pages = "1910--1915",

booktitle = "2017 American Control Conference (ACC)",

note = "2017 American Control Conference<br/>, ACC 2017 ; Conference date: 24-05-2017 Through 26-05-2017",

}

Hoffmann, C, Isler, A & Rostalski, P 2017, A Factor Graph Approach to Parameter Identification for Affine LPV Systems. in 2017 American Control Conference (ACC)., 7963231, Proceedings of the American Control Conference, IEEE, S. 1910-1915, 2017 American Control Conference
, Seattle, Washington, USA / Vereinigte Staaten, 24.05.17. https://doi.org/10.23919/ACC.2017.7963231

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PY - 2017/6/29

Y1 - 2017/6/29

N2 - Factor graphs are a versatile graphical representation of factorizable functions. As a probabilistic graphical model they allow to visualize conditional independence, which can be exploited for efficiently solving inference problems by means of message passing along the nodes of the graph. In this paper, a novel factor graph formulation of the expectation maximization-based estimation technique for affine linear parameter-varying system identification is presented. Furthermore, a recursive reformulation of the algorithm suitable for tracking time-varying changes both accounted and unaccounted for by a pre-defined linear parameter-varying system description is immediate from its factor graph-based formulation.

AB - Factor graphs are a versatile graphical representation of factorizable functions. As a probabilistic graphical model they allow to visualize conditional independence, which can be exploited for efficiently solving inference problems by means of message passing along the nodes of the graph. In this paper, a novel factor graph formulation of the expectation maximization-based estimation technique for affine linear parameter-varying system identification is presented. Furthermore, a recursive reformulation of the algorithm suitable for tracking time-varying changes both accounted and unaccounted for by a pre-defined linear parameter-varying system description is immediate from its factor graph-based formulation.

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DO - 10.23919/ACC.2017.7963231

M3 - Conference contribution

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SN - 978-1-5090-4583-9

T3 - Proceedings of the American Control Conference

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BT - 2017 American Control Conference (ACC)

PB - IEEE

T2 - 2017 American Control Conference<br/>

Y2 - 24 May 2017 through 26 May 2017

ER -

A Factor Graph Approach to Parameter Identification for Affine LPV Systems

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