Modeling and Fuzzy Command of a Wind Generator

Nejib Hamrouni; Amel Ghobber; Moncef Jraidi; Ahmed Dhouib

doi:doi:10.11648/j.cssp.20170604.11

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Modeling and Fuzzy Command of a Wind Generator

Nejib Hamrouni, Amel Ghobber, Moncef Jraidi, Ahmed Dhouib

Published in Science Journal of Circuits, Systems and Signal Processing (Volume 6, Issue 4)

Received: 14 November 2017 Accepted: 30 November 2017 Published: 2 January 2018

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Abstract

A problem of mechanical modeling and robustly stabilization of a wind generator is considered. To overcome the non-linearity of the system, the model of the wind generator is approximated by a Takagi-Sugeno fuzzy model. To stabilize the obtained fuzzy model, two command approaches were developed. They are the fuzzy controller using the parallel distributed compensation (PDC) and the H_∞ controller based-fuzzy observer. Numerical optimization problems using linear matrix inequality (LMI) and convex techniques are used to analyze the stability of the wind generator. Finally, simulation examples illustrating the control performance and dynamic behavior of the wind generator under various command approaches are presented.

Published in	Science Journal of Circuits, Systems and Signal Processing (Volume 6, Issue 4)
DOI	10.11648/j.cssp.20170604.11
Page(s)	35-43
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Modeling, TS-Fuzzy Control, H∞ Command, LMI Approach, Stability

References

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APA Style

Nejib Hamrouni, Amel Ghobber, Moncef Jraidi, Ahmed Dhouib. (2018). Modeling and Fuzzy Command of a Wind Generator. Science Journal of Circuits, Systems and Signal Processing, 6(4), 35-43. https://doi.org/10.11648/j.cssp.20170604.11

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ACS Style

Nejib Hamrouni; Amel Ghobber; Moncef Jraidi; Ahmed Dhouib. Modeling and Fuzzy Command of a Wind Generator. Sci. J. Circuits Syst. Signal Process. 2018, 6(4), 35-43. doi: 10.11648/j.cssp.20170604.11

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AMA Style

Nejib Hamrouni, Amel Ghobber, Moncef Jraidi, Ahmed Dhouib. Modeling and Fuzzy Command of a Wind Generator. Sci J Circuits Syst Signal Process. 2018;6(4):35-43. doi: 10.11648/j.cssp.20170604.11

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@article{10.11648/j.cssp.20170604.11,
  author = {Nejib Hamrouni and Amel Ghobber and Moncef Jraidi and Ahmed Dhouib},
  title = {Modeling and Fuzzy Command of a Wind Generator},
  journal = {Science Journal of Circuits, Systems and Signal Processing},
  volume = {6},
  number = {4},
  pages = {35-43},
  doi = {10.11648/j.cssp.20170604.11},
  url = {https://doi.org/10.11648/j.cssp.20170604.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cssp.20170604.11},
  abstract = {A problem of mechanical modeling and robustly stabilization of a wind generator is considered. To overcome the non-linearity of the system, the model of the wind generator is approximated by a Takagi-Sugeno fuzzy model. To stabilize the obtained fuzzy model, two command approaches were developed. They are the fuzzy controller using the parallel distributed compensation (PDC) and the H∞ controller based-fuzzy observer. Numerical optimization problems using linear matrix inequality (LMI) and convex techniques are used to analyze the stability of the wind generator. Finally, simulation examples illustrating the control performance and dynamic behavior of the wind generator under various command approaches are presented.},
 year = {2018}
}

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TY  - JOUR
T1  - Modeling and Fuzzy Command of a Wind Generator
AU  - Nejib Hamrouni
AU  - Amel Ghobber
AU  - Moncef Jraidi
AU  - Ahmed Dhouib
Y1  - 2018/01/02
PY  - 2018
N1  - https://doi.org/10.11648/j.cssp.20170604.11
DO  - 10.11648/j.cssp.20170604.11
T2  - Science Journal of Circuits, Systems and Signal Processing
JF  - Science Journal of Circuits, Systems and Signal Processing
JO  - Science Journal of Circuits, Systems and Signal Processing
SP  - 35
EP  - 43
PB  - Science Publishing Group
SN  - 2326-9073
UR  - https://doi.org/10.11648/j.cssp.20170604.11
AB  - A problem of mechanical modeling and robustly stabilization of a wind generator is considered. To overcome the non-linearity of the system, the model of the wind generator is approximated by a Takagi-Sugeno fuzzy model. To stabilize the obtained fuzzy model, two command approaches were developed. They are the fuzzy controller using the parallel distributed compensation (PDC) and the H∞ controller based-fuzzy observer. Numerical optimization problems using linear matrix inequality (LMI) and convex techniques are used to analyze the stability of the wind generator. Finally, simulation examples illustrating the control performance and dynamic behavior of the wind generator under various command approaches are presented.
VL  - 6
IS  - 4
ER  -

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Author Information

Nejib Hamrouni

Department of Electric, Science Faculty of Tunis, University of Tunis El Manar, Tunis, Tunisia
Amel Ghobber

Department of Electric, Science Faculty of Tunis, University of Tunis El Manar, Tunis, Tunisia
Moncef Jraidi

Department of Electric, Science Faculty of Tunis, University of Tunis El Manar, Tunis, Tunisia
Ahmed Dhouib

Department of Electric, Science Faculty of Tunis, University of Tunis El Manar, Tunis, Tunisia

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Plain Text BibTeX RIS

APA Style

Nejib Hamrouni, Amel Ghobber, Moncef Jraidi, Ahmed Dhouib. (2018). Modeling and Fuzzy Command of a Wind Generator. Science Journal of Circuits, Systems and Signal Processing, 6(4), 35-43. https://doi.org/10.11648/j.cssp.20170604.11

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ACS Style

Nejib Hamrouni; Amel Ghobber; Moncef Jraidi; Ahmed Dhouib. Modeling and Fuzzy Command of a Wind Generator. Sci. J. Circuits Syst. Signal Process. 2018, 6(4), 35-43. doi: 10.11648/j.cssp.20170604.11

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AMA Style

Nejib Hamrouni, Amel Ghobber, Moncef Jraidi, Ahmed Dhouib. Modeling and Fuzzy Command of a Wind Generator. Sci J Circuits Syst Signal Process. 2018;6(4):35-43. doi: 10.11648/j.cssp.20170604.11

Copy | Download

@article{10.11648/j.cssp.20170604.11,
  author = {Nejib Hamrouni and Amel Ghobber and Moncef Jraidi and Ahmed Dhouib},
  title = {Modeling and Fuzzy Command of a Wind Generator},
  journal = {Science Journal of Circuits, Systems and Signal Processing},
  volume = {6},
  number = {4},
  pages = {35-43},
  doi = {10.11648/j.cssp.20170604.11},
  url = {https://doi.org/10.11648/j.cssp.20170604.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cssp.20170604.11},
  abstract = {A problem of mechanical modeling and robustly stabilization of a wind generator is considered. To overcome the non-linearity of the system, the model of the wind generator is approximated by a Takagi-Sugeno fuzzy model. To stabilize the obtained fuzzy model, two command approaches were developed. They are the fuzzy controller using the parallel distributed compensation (PDC) and the H∞ controller based-fuzzy observer. Numerical optimization problems using linear matrix inequality (LMI) and convex techniques are used to analyze the stability of the wind generator. Finally, simulation examples illustrating the control performance and dynamic behavior of the wind generator under various command approaches are presented.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - Modeling and Fuzzy Command of a Wind Generator
AU  - Nejib Hamrouni
AU  - Amel Ghobber
AU  - Moncef Jraidi
AU  - Ahmed Dhouib
Y1  - 2018/01/02
PY  - 2018
N1  - https://doi.org/10.11648/j.cssp.20170604.11
DO  - 10.11648/j.cssp.20170604.11
T2  - Science Journal of Circuits, Systems and Signal Processing
JF  - Science Journal of Circuits, Systems and Signal Processing
JO  - Science Journal of Circuits, Systems and Signal Processing
SP  - 35
EP  - 43
PB  - Science Publishing Group
SN  - 2326-9073
UR  - https://doi.org/10.11648/j.cssp.20170604.11
AB  - A problem of mechanical modeling and robustly stabilization of a wind generator is considered. To overcome the non-linearity of the system, the model of the wind generator is approximated by a Takagi-Sugeno fuzzy model. To stabilize the obtained fuzzy model, two command approaches were developed. They are the fuzzy controller using the parallel distributed compensation (PDC) and the H∞ controller based-fuzzy observer. Numerical optimization problems using linear matrix inequality (LMI) and convex techniques are used to analyze the stability of the wind generator. Finally, simulation examples illustrating the control performance and dynamic behavior of the wind generator under various command approaches are presented.
VL  - 6
IS  - 4
ER  -

Copy | Download