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A two-level estimator for time varying parameters

Wittenmark, Björn LU (1979) In Automatica 15(1). p.85-89
Abstract
A crucial part in an adaptive control system is the estimation of the unknown parameters of the process. The estimation is often done using a Kalman filter or an Extended Kalman filter. These estimators give good results if the parameters are not varying too fast. When the parameters are varying fast there are difficulties for the estimator to follow the variations.



This paper outlines a new approach to the estimation problem. The new estimator consists of two parts. One conventional Kalman filter for fine estimation and one estimator for coarse estimation. The coarse estimator consists of a finite number of fixed a priori models and a decision mechanism which points out the model which best fits the data.

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A crucial part in an adaptive control system is the estimation of the unknown parameters of the process. The estimation is often done using a Kalman filter or an Extended Kalman filter. These estimators give good results if the parameters are not varying too fast. When the parameters are varying fast there are difficulties for the estimator to follow the variations.



This paper outlines a new approach to the estimation problem. The new estimator consists of two parts. One conventional Kalman filter for fine estimation and one estimator for coarse estimation. The coarse estimator consists of a finite number of fixed a priori models and a decision mechanism which points out the model which best fits the data.



The paper describes the two-level estimator and discusses its properties. Some numerical examples illustrate the behavior of the estimator. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Adaptive systems, parameter estimation, real time identification, Kalman filters
in
Automatica
volume
15
issue
1
pages
85 - 89
publisher
Pergamon
external identifiers
  • Scopus:0018289763
ISSN
0005-1098
DOI
10.1016/0005-1098(79)90089-X
language
English
LU publication?
yes
id
38dfc5d3-f877-4bd3-8c9f-31636fe0eac7 (old id 4820774)
date added to LUP
2014-12-05 09:37:47
date last changed
2016-10-13 04:55:41
@misc{38dfc5d3-f877-4bd3-8c9f-31636fe0eac7,
  abstract     = {A crucial part in an adaptive control system is the estimation of the unknown parameters of the process. The estimation is often done using a Kalman filter or an Extended Kalman filter. These estimators give good results if the parameters are not varying too fast. When the parameters are varying fast there are difficulties for the estimator to follow the variations.<br/><br>
<br/><br>
This paper outlines a new approach to the estimation problem. The new estimator consists of two parts. One conventional Kalman filter for fine estimation and one estimator for coarse estimation. The coarse estimator consists of a finite number of fixed a priori models and a decision mechanism which points out the model which best fits the data.<br/><br>
<br/><br>
The paper describes the two-level estimator and discusses its properties. Some numerical examples illustrate the behavior of the estimator.},
  author       = {Wittenmark, Björn},
  issn         = {0005-1098},
  keyword      = {Adaptive systems,parameter estimation,real time identification,Kalman filters},
  language     = {eng},
  number       = {1},
  pages        = {85--89},
  publisher    = {ARRAY(0x8c0d200)},
  series       = {Automatica},
  title        = {A two-level estimator for time varying parameters},
  url          = {http://dx.doi.org/10.1016/0005-1098(79)90089-X},
  volume       = {15},
  year         = {1979},
}