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System Identification using LQG-Balanced Model Reduction,

Johansson, Rolf LU orcid (2002) IEEE Conference on Decision and Control 1. p.258-263
Abstract
System identification of linear multivariable dy-namic models based on discrete-time data can be performed using a algorithm combining linear regression and LQG-balanced model reduction. The approach is applicable also to unstable system dynamics and it provides balanced models for optimal linear prediction and control.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
identification, linear quadratic Gaussian control, linear systems, multivariable systems, stability statistical analysis, prediction theory, reduced order systems, discrete time systems
host publication
Proceedings of the 41st IEEE Conference on Decision and Control, 2002
volume
1
pages
258 - 263
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE Conference on Decision and Control
conference location
Las Vegas, NV, United States
conference dates
2002-12-10 - 2002-12-13
external identifiers
  • wos:000181352300045
  • scopus:0036994268
ISSN
0191-2216
ISBN
0-7803-7516-5
language
English
LU publication?
yes
id
e6cc714c-e5a2-4fe6-8b7c-cfbe53c52e87 (old id 537741)
alternative location
http://ieeexplore.ieee.org/iel5/8437/26566/01184501.pdf
date added to LUP
2016-04-01 15:47:08
date last changed
2022-01-28 07:05:54
@inproceedings{e6cc714c-e5a2-4fe6-8b7c-cfbe53c52e87,
  abstract     = {{System identification of linear multivariable dy-namic models based on discrete-time data can be performed using a algorithm combining linear regression and LQG-balanced model reduction. The approach is applicable also to unstable system dynamics and it provides balanced models for optimal linear prediction and control.}},
  author       = {{Johansson, Rolf}},
  booktitle    = {{Proceedings of the 41st IEEE Conference on Decision and Control, 2002}},
  isbn         = {{0-7803-7516-5}},
  issn         = {{0191-2216}},
  keywords     = {{identification; linear quadratic Gaussian control; linear systems; multivariable systems; stability    statistical analysis; prediction theory; reduced order systems; discrete time systems}},
  language     = {{eng}},
  pages        = {{258--263}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{System Identification using LQG-Balanced Model Reduction,}},
  url          = {{https://lup.lub.lu.se/search/files/4471122/625689.pdf}},
  volume       = {{1}},
  year         = {{2002}},
}