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Observer Synthesis for Switched Discrete-Time Linear Systems using Relaxed Dynamic Programming

Alriksson, Peter LU and Rantzer, Anders LU orcid (2006) 17th International Symposium on Mathematical Theory of Networks and Systems, 2006
Abstract
In this paper, state estimation for Switched Discrete-Time Linear

Systems is performed using relaxed dynamic programming. Taking the Bayesian point of view, the estimation problem is transformed into an infinite dimension al optimization problem. The optimization problem is then solved using relaxed dynamic programming. The estimate of both the mode and the continuous state can then be computed from the value-function. From an unknown initial state the estimation error goes to zero as more measurements are collected.
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Contribution to conference
publication status
published
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conference name
17th International Symposium on Mathematical Theory of Networks and Systems, 2006
conference location
Kyoto, Japan
conference dates
2006-07-24 - 2006-07-28
language
English
LU publication?
yes
id
36746938-66cb-4b81-ac45-53b59ab6ba2b (old id 929458)
date added to LUP
2016-04-04 14:07:21
date last changed
2018-11-21 21:18:25
@misc{36746938-66cb-4b81-ac45-53b59ab6ba2b,
  abstract     = {{In this paper, state estimation for Switched Discrete-Time Linear<br/><br>
Systems is performed using relaxed dynamic programming. Taking the Bayesian point of view, the estimation problem is transformed into an infinite dimension al optimization problem. The optimization problem is then solved using relaxed dynamic programming. The estimate of both the mode and the continuous state can then be computed from the value-function. From an unknown initial state the estimation error goes to zero as more measurements are collected.}},
  author       = {{Alriksson, Peter and Rantzer, Anders}},
  language     = {{eng}},
  title        = {{Observer Synthesis for Switched Discrete-Time Linear Systems using Relaxed Dynamic Programming}},
  url          = {{https://lup.lub.lu.se/search/files/6285674/8866193.pdf}},
  year         = {{2006}},
}