System Identification with Constraints

Tom D'Haene

Abstract

Stability and Passivity of the identified model is crucial in simulation and prediction applications. This paper proposes a two step procedure that generates guaranteed stable or passive transfer function models from noisy data. It consists of an unconstrained optimal noise removal step followed by a stability/passivity enforcement of the unconstrained model. The proposed method is applicable to continuous-time as well as discrete-time and multi-input, multivariable systems.

Original language	English
Title of host publication	15th ERNSI Workshop on System Identification, September 20-21, 2006. Linköping, Sweden.
Publication status	Published - 20 Sept 2006
Event	Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet - Stockholm, Sweden Duration: 21 Sept 2009 → 25 Sept 2009

Conference

Conference	Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet
Country/Territory	Sweden
City	Stockholm
Period	21/09/09 → 25/09/09

Keywords

System Identification

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Persistent link

15th ERNSI Workshop on System Identification
Enqvist, M. (Speaker)
20 Sept 2006 → 21 Sept 2006
Activity: Talk or presentation › Talk or presentation at a workshop/seminar
15th ERNSI Workshop on System Identification
Paduart, J. (Speaker)
20 Sept 2006 → 21 Sept 2006
Activity: Talk or presentation › Talk or presentation at a workshop/seminar
15th ERNSI Workshop on System Identification
D'Haene, T. (Speaker)
20 Sept 2006 → 21 Sept 2006
Activity: Talk or presentation › Talk or presentation at a workshop/seminar

Cite this

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title = "System Identification with Constraints",

abstract = "Stability and Passivity of the identified model is crucial in simulation and prediction applications. This paper proposes a two step procedure that generates guaranteed stable or passive transfer function models from noisy data. It consists of an unconstrained optimal noise removal step followed by a stability/passivity enforcement of the unconstrained model. The proposed method is applicable to continuous-time as well as discrete-time and multi-input, multivariable systems.",

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author = "Tom D'Haene",

year = "2006",

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language = "English",

booktitle = "15th ERNSI Workshop on System Identification, September 20-21, 2006. Link{\"o}ping, Sweden.",

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AU - D'Haene, Tom

PY - 2006/9/20

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N2 - Stability and Passivity of the identified model is crucial in simulation and prediction applications. This paper proposes a two step procedure that generates guaranteed stable or passive transfer function models from noisy data. It consists of an unconstrained optimal noise removal step followed by a stability/passivity enforcement of the unconstrained model. The proposed method is applicable to continuous-time as well as discrete-time and multi-input, multivariable systems.

AB - Stability and Passivity of the identified model is crucial in simulation and prediction applications. This paper proposes a two step procedure that generates guaranteed stable or passive transfer function models from noisy data. It consists of an unconstrained optimal noise removal step followed by a stability/passivity enforcement of the unconstrained model. The proposed method is applicable to continuous-time as well as discrete-time and multi-input, multivariable systems.

KW - System Identification

M3 - Meeting abstract (Book)

BT - 15th ERNSI Workshop on System Identification, September 20-21, 2006. Linköping, Sweden.

T2 - Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet

Y2 - 21 September 2009 through 25 September 2009

ER -

System Identification with Constraints

Abstract

Conference

Keywords

Handle.net

Fingerprint

Activities

15th ERNSI Workshop on System Identification

15th ERNSI Workshop on System Identification

15th ERNSI Workshop on System Identification

Cite this