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DOKOUPIL, J.; PIVOŇKA, P.
Original Title
Adaptive Nonlinear Model Predictive Control Based on Wiener Model
English Title
Type
Peer-reviewed article not indexed in WoS or Scopus
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.
English abstract
Keywords
nonlinear model predictive control, time-varying systems, Wiener model, Levenberg-Marquardt method
Key words in English
Authors
RIV year
2012
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
Volume
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" }