A Subspace Identification Algorithm for Descriptor Systems

Jose A. Ramos; Marc Moonen; Bart De Moor; Shaohua Tan

doi:10.1016/0167-6911(92)90039-U

A Subspace Identification Algorithm for Descriptor Systems

Jose A. Ramos
, Marc Moonen
, Bart De Moor
, Shaohua Tan

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

16 Scopus citations

Abstract

We present a subspace algorithm for identifying state space models for descriptor systems, directly from input/output data. The subspace algorithm avoids the use of Markov parameters which are difficult to estimate in practice. It also applies to unstable systems without difficulty.

Original language	American English
Journal	Systems & Control Letters
Volume	19
DOIs	https://doi.org/10.1016/0167-6911(92)90039-U
State	Published - Jul 1 1992

Keywords

Linear systems
descriptor systems
state space models
subspace algorithms
systems identification

Disciplines

Computer Sciences

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10.1016/0167-6911(92)90039-ULicense: Unspecified

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title = "A Subspace Identification Algorithm for Descriptor Systems",

abstract = " We present a subspace algorithm for identifying state space models for descriptor systems, directly from input/output data. The subspace algorithm avoids the use of Markov parameters which are difficult to estimate in practice. It also applies to unstable systems without difficulty.",

keywords = "Linear systems, descriptor systems, state space models, subspace algorithms, systems identification",

author = "Ramos, \{Jose A.\} and Marc Moonen and Moor, \{Bart De\} and Shaohua Tan",

year = "1992",

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day = "1",

doi = "10.1016/0167-6911(92)90039-U",

language = "American English",

volume = "19",

journal = "Systems \& Control Letters",

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T1 - A Subspace Identification Algorithm for Descriptor Systems

AU - Ramos, Jose A.

AU - Moonen, Marc

AU - Moor, Bart De

AU - Tan, Shaohua

PY - 1992/7/1

Y1 - 1992/7/1

N2 - We present a subspace algorithm for identifying state space models for descriptor systems, directly from input/output data. The subspace algorithm avoids the use of Markov parameters which are difficult to estimate in practice. It also applies to unstable systems without difficulty.

AB - We present a subspace algorithm for identifying state space models for descriptor systems, directly from input/output data. The subspace algorithm avoids the use of Markov parameters which are difficult to estimate in practice. It also applies to unstable systems without difficulty.

KW - Linear systems

KW - descriptor systems

KW - state space models

KW - subspace algorithms

KW - systems identification

UR - https://nsuworks.nova.edu/gscis_facarticles/423

U2 - 10.1016/0167-6911(92)90039-U

DO - 10.1016/0167-6911(92)90039-U

M3 - Article

SN - 0167-6911

VL - 19

JO - Systems & Control Letters

JF - Systems & Control Letters

ER -

A Subspace Identification Algorithm for Descriptor Systems

Abstract

Keywords

Disciplines

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