Detail publikace

A Levenberg-Marquardt Method for Nonlinear Model Predictive Control Design

DOKOUPIL, J. PIVOŇKA, P. BURLAK, V.

Originální název

A Levenberg-Marquardt Method for Nonlinear Model Predictive Control Design

Anglický název

A Levenberg-Marquardt Method for Nonlinear Model Predictive Control Design

Jazyk

en

Originální abstrakt

This article deals with a nonlinear model predictive control design (NMPC) which applies numerical optimization using the Levenberg-Marquardt method in iterative batch mode adaptation. The proposed approach enables asymptotic tracking of a reference trajectory by a prediction of a general nonlinear model. Investigation of the properties of the NMPC is performed using the Wiener nonlinear model which is suitable to describe an unknown process dynamics. The work therefore also seeks to formulate the optimal prediction of Wiener model output in state space representation.

Anglický abstrakt

This article deals with a nonlinear model predictive control design (NMPC) which applies numerical optimization using the Levenberg-Marquardt method in iterative batch mode adaptation. The proposed approach enables asymptotic tracking of a reference trajectory by a prediction of a general nonlinear model. Investigation of the properties of the NMPC is performed using the Wiener nonlinear model which is suitable to describe an unknown process dynamics. The work therefore also seeks to formulate the optimal prediction of Wiener model output in state space representation.

Dokumenty

BibTex


@inproceedings{BUT74597,
  author="Jakub {Dokoupil} and Petr {Pivoňka} and Vladimír {Burlak}",
  title="A Levenberg-Marquardt Method for Nonlinear Model Predictive Control Design",
  annote="This article deals with a nonlinear model predictive control design (NMPC) which applies numerical optimization using the Levenberg-Marquardt method in iterative batch mode adaptation. The proposed approach enables asymptotic tracking of a reference trajectory by a prediction of a general nonlinear model. Investigation of the properties of the NMPC is performed using the Wiener nonlinear model which is suitable to describe an unknown process dynamics. The work therefore also seeks to formulate the optimal prediction of Wiener model output in state space representation.",
  address="DAAAM International Vienna",
  booktitle="Annals & Proceedings of 22nd DAAAM World Symposiums",
  chapter="74597",
  edition="2011",
  howpublished="print",
  institution="DAAAM International Vienna",
  year="2011",
  month="november",
  pages="861--862",
  publisher="DAAAM International Vienna",
  type="conference paper"
}