GENETIC AND ELLIPSOID ALGORITHMS FOR NONLINEAR PREDICTIVE CONTROL

Kaouther Laabidi, Faouzi Bouani, Mekki Ksouri

Abstract

This paper deals with the constrained predictive control of nonlinear systems. Artificial Neural Networks (ANN) are used as a process model. The control law is derived by minimizing a non convex criterion. The optimization problem is solved using Ellipsoid and genetic algorithms. The structure and operators of the combining two algorithms have been specifically developed for control design problem. Simulation results are presented to illustrate the performances of the proposed predictive controller.

References

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Paper Citation


in Harvard Style

Laabidi K., Bouani F. and Ksouri M. (2005). GENETIC AND ELLIPSOID ALGORITHMS FOR NONLINEAR PREDICTIVE CONTROL . In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 972-8865-29-5, pages 288-291. DOI: 10.5220/0001181302880291


in Bibtex Style

@conference{icinco05,
author={Kaouther Laabidi and Faouzi Bouani and Mekki Ksouri},
title={GENETIC AND ELLIPSOID ALGORITHMS FOR NONLINEAR PREDICTIVE CONTROL},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2005},
pages={288-291},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001181302880291},
isbn={972-8865-29-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - GENETIC AND ELLIPSOID ALGORITHMS FOR NONLINEAR PREDICTIVE CONTROL
SN - 972-8865-29-5
AU - Laabidi K.
AU - Bouani F.
AU - Ksouri M.
PY - 2005
SP - 288
EP - 291
DO - 10.5220/0001181302880291