Publication detail

Adaptive Nonlinear Model Predictive Control Based on Wiener Model

DOKOUPIL, J. PIVOŇKA, P.

Original Title

Adaptive Nonlinear Model Predictive Control Based on Wiener Model

Type

journal article - other

Language

English

Original Abstract

This article deals with a nonlinear model predictive control design (NMPC) with closed loop identification 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 adaptive NMPC is performed using the Wiener nonlinear model which is considered to be suitable for representing a wide range of nonlinear process behavior. Although it requires little more effort in development than a standard pseudolinear model from the output error class, it offers better approximation of systems with highly nonlinear gains. The work therefore also seeks to formulate the optimal prediction of Wiener model output in both state space and input-output representation.

Keywords

nonlinear model predictive control, time-varying systems, Wiener model, Levenberg-Marquardt method

Authors

DOKOUPIL, J.; PIVOŇKA, P.

RIV year

2011

Released

22. 11. 2011

Publisher

DAAAM International Vienn

Location

TU Wien Karlsplatz 13/311 A-1040 Vienna Austria

ISBN

1726-9687

Periodical

DAAAM International Scientific Book

Year of study

10

Number

11

State

Republic of Austria

Pages from

417

Pages to

424

Pages count

8

BibTex

@article{BUT74600,
  author="Jakub {Dokoupil} and Petr {Pivoňka}",
  title="Adaptive Nonlinear Model Predictive Control Based on Wiener Model",
  journal="DAAAM International Scientific Book",
  year="2011",
  volume="10",
  number="11",
  pages="417--424",
  issn="1726-9687"
}