Balanced Truncation for a General Class of Discrete-Time Markov Jump Linear Systems

Georgios Kotsalis; Anders Rantzer

Balanced Truncation for a General Class of Discrete-Time Markov Jump Linear Systems

Georgios Kotsalis, Anders Rantzer

Department of Automatic Control

Research output: Contribution to conference › Paper, not in proceeding › peer-review

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Abstract

This paper develops a generalization of the balanced truncation algorithm applicable to discrete-time Markov jump linear systems. The approximation error, which is captured by means of the stochastic L2 gain, is bounded from above by twice the sum of singular numbers associated to the truncated states of each mode.

Original language	English
Publication status	Published - 2008
Event	American Control Conference 2008 - Seattle, Wa, United States Duration: 2008 Jun 11 → 2008 Jun 13

Conference

Conference	American Control Conference 2008
Country/Territory	United States
City	Seattle, Wa
Period	2008/06/11 → 2008/06/13

Subject classification (UKÄ)

Control Engineering

Free keywords

markov jump
model reduction
hybrid systems

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kots_08

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title = "Balanced Truncation for a General Class of Discrete-Time Markov Jump Linear Systems",

abstract = "This paper develops a generalization of the balanced truncation algorithm applicable to discrete-time Markov jump linear systems. The approximation error, which is captured by means of the stochastic L2 gain, is bounded from above by twice the sum of singular numbers associated to the truncated states of each mode.",

keywords = "markov jump, model reduction, hybrid systems",

author = "Georgios Kotsalis and Anders Rantzer",

year = "2008",

language = "English",

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AU - Rantzer, Anders

PY - 2008

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N2 - This paper develops a generalization of the balanced truncation algorithm applicable to discrete-time Markov jump linear systems. The approximation error, which is captured by means of the stochastic L2 gain, is bounded from above by twice the sum of singular numbers associated to the truncated states of each mode.

AB - This paper develops a generalization of the balanced truncation algorithm applicable to discrete-time Markov jump linear systems. The approximation error, which is captured by means of the stochastic L2 gain, is bounded from above by twice the sum of singular numbers associated to the truncated states of each mode.

KW - markov jump

KW - model reduction

KW - hybrid systems

M3 - Paper, not in proceeding

T2 - American Control Conference 2008

Y2 - 11 June 2008 through 13 June 2008

ER -

Balanced Truncation for a General Class of Discrete-Time Markov Jump Linear Systems

Abstract

Conference

Subject classification (UKÄ)

Free keywords

Access to Document

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Cite this