Fractional kalman filter algorithm for the states parameters and order of fractional system estimation

• Volume: 16, Issue: 1, page 129-140
• ISSN: 1641-876X

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Abstract

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This paper presents a generalization of the Kalman filter for linear and nonlinear fractional order discrete state-space systems. Linear and nonlinear discrete fractional order state-space systems are also introduced. The simplified kalman filter for the linear case is called the fractional Kalman filter and its nonlinear extension is named the extended fractional Kalman filter. The background and motivations for using such techniques are given, and some algorithms are discussed. The paper also shows a simple numerical example of linear state estimation. Finally, as an example of nonlinear estimation, the paper discusses the possibility of using these algorithms for parameters and fractional order estimation for fractional order systems. Numerical examples of the use of these algorithms in a general nonlinear case are presented.

How to cite

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Sierociuk, Dominik, and Dzieliński, Andrzej. "Fractional kalman filter algorithm for the states parameters and order of fractional system estimation." International Journal of Applied Mathematics and Computer Science 16.1 (2006): 129-140. <http://eudml.org/doc/207770>.

@article{Sierociuk2006,
abstract = {This paper presents a generalization of the Kalman filter for linear and nonlinear fractional order discrete state-space systems. Linear and nonlinear discrete fractional order state-space systems are also introduced. The simplified kalman filter for the linear case is called the fractional Kalman filter and its nonlinear extension is named the extended fractional Kalman filter. The background and motivations for using such techniques are given, and some algorithms are discussed. The paper also shows a simple numerical example of linear state estimation. Finally, as an example of nonlinear estimation, the paper discusses the possibility of using these algorithms for parameters and fractional order estimation for fractional order systems. Numerical examples of the use of these algorithms in a general nonlinear case are presented.},
author = {Sierociuk, Dominik, Dzieliński, Andrzej},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {linebreak extended fractional Kalman filter; discrete fractional state-space systems; parameters estimation; fractional Kalman filter; order estimation; extended fractional Kalman filter},
language = {eng},
number = {1},
pages = {129-140},
title = {Fractional kalman filter algorithm for the states parameters and order of fractional system estimation},
url = {http://eudml.org/doc/207770},
volume = {16},
year = {2006},
}

TY - JOUR
AU - Sierociuk, Dominik
AU - Dzieliński, Andrzej
TI - Fractional kalman filter algorithm for the states parameters and order of fractional system estimation
JO - International Journal of Applied Mathematics and Computer Science
PY - 2006
VL - 16
IS - 1
SP - 129
EP - 140
AB - This paper presents a generalization of the Kalman filter for linear and nonlinear fractional order discrete state-space systems. Linear and nonlinear discrete fractional order state-space systems are also introduced. The simplified kalman filter for the linear case is called the fractional Kalman filter and its nonlinear extension is named the extended fractional Kalman filter. The background and motivations for using such techniques are given, and some algorithms are discussed. The paper also shows a simple numerical example of linear state estimation. Finally, as an example of nonlinear estimation, the paper discusses the possibility of using these algorithms for parameters and fractional order estimation for fractional order systems. Numerical examples of the use of these algorithms in a general nonlinear case are presented.
LA - eng
KW - linebreak extended fractional Kalman filter; discrete fractional state-space systems; parameters estimation; fractional Kalman filter; order estimation; extended fractional Kalman filter
UR - http://eudml.org/doc/207770
ER -

References

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