Nonlinear system identification using heterogeneous multiple models

Rodolfo Orjuela; Benoît Marx; José Ragot; Didier Maquin

International Journal of Applied Mathematics and Computer Science (2013)

  • Volume: 23, Issue: 1, page 103-115
  • ISSN: 1641-876X

Abstract

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Multiple models are recognised by their abilities to accurately describe nonlinear dynamic behaviours of a wide variety of nonlinear systems with a tractable model in control engineering problems. Multiple models are built by the interpolation of a set of submodels according to a particular aggregation mechanism, with the heterogeneous multiple model being of particular interest. This multiple model is characterized by the use of heterogeneous submodels in the sense that their state spaces are not the same and consequently they can be of various dimensions. Thanks to this feature, the complexity of the submodels can be well adapted to that of the nonlinear system introducing flexibility and generality in the modelling stage. This paper deals with off-line identification of nonlinear systems based on heterogeneous multiple models. Three optimisation criteria (global, local and combined) are investigated to obtain the submodel parameters according to the expected modelling performances. Particular attention is paid to the potential problems encountered in the identification procedure with a special focus on an undesirable phenomenon called the no output tracking effect. The origin of this difficulty is explained and an effective solution is suggested to overcome this problem in the identification task. The abilities of the model are finally illustrated via relevant identification examples showing the effectiveness of the proposed methods.

How to cite

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Rodolfo Orjuela, et al. "Nonlinear system identification using heterogeneous multiple models." International Journal of Applied Mathematics and Computer Science 23.1 (2013): 103-115. <http://eudml.org/doc/251337>.

@article{RodolfoOrjuela2013,
abstract = {Multiple models are recognised by their abilities to accurately describe nonlinear dynamic behaviours of a wide variety of nonlinear systems with a tractable model in control engineering problems. Multiple models are built by the interpolation of a set of submodels according to a particular aggregation mechanism, with the heterogeneous multiple model being of particular interest. This multiple model is characterized by the use of heterogeneous submodels in the sense that their state spaces are not the same and consequently they can be of various dimensions. Thanks to this feature, the complexity of the submodels can be well adapted to that of the nonlinear system introducing flexibility and generality in the modelling stage. This paper deals with off-line identification of nonlinear systems based on heterogeneous multiple models. Three optimisation criteria (global, local and combined) are investigated to obtain the submodel parameters according to the expected modelling performances. Particular attention is paid to the potential problems encountered in the identification procedure with a special focus on an undesirable phenomenon called the no output tracking effect. The origin of this difficulty is explained and an effective solution is suggested to overcome this problem in the identification task. The abilities of the model are finally illustrated via relevant identification examples showing the effectiveness of the proposed methods.},
author = {Rodolfo Orjuela, Benoît Marx, José Ragot, Didier Maquin},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {nonlinear system identification; multiple models; heterogeneous submodels},
language = {eng},
number = {1},
pages = {103-115},
title = {Nonlinear system identification using heterogeneous multiple models},
url = {http://eudml.org/doc/251337},
volume = {23},
year = {2013},
}

TY - JOUR
AU - Rodolfo Orjuela
AU - Benoît Marx
AU - José Ragot
AU - Didier Maquin
TI - Nonlinear system identification using heterogeneous multiple models
JO - International Journal of Applied Mathematics and Computer Science
PY - 2013
VL - 23
IS - 1
SP - 103
EP - 115
AB - Multiple models are recognised by their abilities to accurately describe nonlinear dynamic behaviours of a wide variety of nonlinear systems with a tractable model in control engineering problems. Multiple models are built by the interpolation of a set of submodels according to a particular aggregation mechanism, with the heterogeneous multiple model being of particular interest. This multiple model is characterized by the use of heterogeneous submodels in the sense that their state spaces are not the same and consequently they can be of various dimensions. Thanks to this feature, the complexity of the submodels can be well adapted to that of the nonlinear system introducing flexibility and generality in the modelling stage. This paper deals with off-line identification of nonlinear systems based on heterogeneous multiple models. Three optimisation criteria (global, local and combined) are investigated to obtain the submodel parameters according to the expected modelling performances. Particular attention is paid to the potential problems encountered in the identification procedure with a special focus on an undesirable phenomenon called the no output tracking effect. The origin of this difficulty is explained and an effective solution is suggested to overcome this problem in the identification task. The abilities of the model are finally illustrated via relevant identification examples showing the effectiveness of the proposed methods.
LA - eng
KW - nonlinear system identification; multiple models; heterogeneous submodels
UR - http://eudml.org/doc/251337
ER -

References

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