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System Identification using LQG-Balanced Model Reduction,

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Author

Summary, in English

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.

Publishing year

2002

Language

English

Pages

258-263

Publication/Series

Proceedings of the 41st IEEE Conference on Decision and Control, 2002

Volume

1

Document type

Conference paper

Publisher

IEEE - Institute of Electrical and Electronics Engineers Inc.

Topic

  • Control Engineering

Keywords

  • identification
  • linear quadratic Gaussian control
  • linear systems
  • multivariable systems
  • stability statistical analysis
  • prediction theory
  • reduced order systems
  • discrete time systems

Conference name

IEEE Conference on Decision and Control

Conference date

2002-12-10 - 2002-12-13

Conference place

Las Vegas, NV, United States

Status

Published

ISBN/ISSN/Other

  • ISSN: 0191-2216
  • ISBN: 0-7803-7516-5