A Subspace Algorithm for Balanced State Space System Identification

Jose A. Ramos; Marc Moonen

doi:10.1109/9.262050

A Subspace Algorithm for Balanced State Space System Identification

Jose A. Ramos
, Marc Moonen

Research output: Contribution to journal › Article › peer-review

31 Scopus citations

Abstract

n an earlier paper ([SI), an algorithm has been introduced for identifying multivariable linear systems directly from input-output data. This new algorithm falls in the class of so-called subspace methods and resembles impulse response based realization algorithms. In this note, we extend this algorithm by incorporating a balancing step, such that the identified model is always in balanced coordinates. With this modification, one obtains a data driven counterpart for Kung’s realization algorithm.

Original language	American English
Journal	IEEE Transactions on Automatic Control
Volume	38
DOIs	https://doi.org/10.1109/9.262050
State	Published - Nov 1 1993

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Computer Sciences

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title = "A Subspace Algorithm for Balanced State Space System Identification",

abstract = " n an earlier paper ([SI), an algorithm has been introduced for identifying multivariable linear systems directly from input-output data. This new algorithm falls in the class of so-called subspace methods and resembles impulse response based realization algorithms. In this note, we extend this algorithm by incorporating a balancing step, such that the identified model is always in balanced coordinates. With this modification, one obtains a data driven counterpart for Kung{\textquoteright}s realization algorithm.",

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AU - Moonen, Marc

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N2 - n an earlier paper ([SI), an algorithm has been introduced for identifying multivariable linear systems directly from input-output data. This new algorithm falls in the class of so-called subspace methods and resembles impulse response based realization algorithms. In this note, we extend this algorithm by incorporating a balancing step, such that the identified model is always in balanced coordinates. With this modification, one obtains a data driven counterpart for Kung’s realization algorithm.

AB - n an earlier paper ([SI), an algorithm has been introduced for identifying multivariable linear systems directly from input-output data. This new algorithm falls in the class of so-called subspace methods and resembles impulse response based realization algorithms. In this note, we extend this algorithm by incorporating a balancing step, such that the identified model is always in balanced coordinates. With this modification, one obtains a data driven counterpart for Kung’s realization algorithm.

UR - https://nsuworks.nova.edu/gscis_facarticles/424

U2 - 10.1109/9.262050

DO - 10.1109/9.262050

M3 - Article

SN - 0018-9286

VL - 38

JO - IEEE Transactions on Automatic Control

JF - IEEE Transactions on Automatic Control

ER -

A Subspace Algorithm for Balanced State Space System Identification

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