Recursive set membership estimation for output-error fractional models with unknown-but-bounded errors
International Journal of Applied Mathematics and Computer Science (2016)
- Volume: 26, Issue: 3, page 543-553
- ISSN: 1641-876X
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topMessaoud Amairi. "Recursive set membership estimation for output-error fractional models with unknown-but-bounded errors." International Journal of Applied Mathematics and Computer Science 26.3 (2016): 543-553. <http://eudml.org/doc/286724>.
@article{MessaoudAmairi2016,
abstract = {This paper presents a new formulation for set-membership parameter estimation of fractional systems. In such a context, the error between the measured data and the output model is supposed to be unknown but bounded with a priori known bounds. The bounded error is specified over measurement noise, rather than over an equation error, which is mainly motivated by experimental considerations. The proposed approach is based on the optimal bounding ellipsoid algorithm for linear output-error fractional models. A numerical example is presented to show effectiveness and discuss results.},
author = {Messaoud Amairi},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {fractional calculus; set membership; estimation; unknown-but-bounded error},
language = {eng},
number = {3},
pages = {543-553},
title = {Recursive set membership estimation for output-error fractional models with unknown-but-bounded errors},
url = {http://eudml.org/doc/286724},
volume = {26},
year = {2016},
}
TY - JOUR
AU - Messaoud Amairi
TI - Recursive set membership estimation for output-error fractional models with unknown-but-bounded errors
JO - International Journal of Applied Mathematics and Computer Science
PY - 2016
VL - 26
IS - 3
SP - 543
EP - 553
AB - This paper presents a new formulation for set-membership parameter estimation of fractional systems. In such a context, the error between the measured data and the output model is supposed to be unknown but bounded with a priori known bounds. The bounded error is specified over measurement noise, rather than over an equation error, which is mainly motivated by experimental considerations. The proposed approach is based on the optimal bounding ellipsoid algorithm for linear output-error fractional models. A numerical example is presented to show effectiveness and discuss results.
LA - eng
KW - fractional calculus; set membership; estimation; unknown-but-bounded error
UR - http://eudml.org/doc/286724
ER -
References
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