Newton projection with proportioning using iterative linear algebra for model predictive control with long prediction horizon
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00328302" target="_blank" >RIV/68407700:21230/19:00328302 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1080/10556788.2019.1571588" target="_blank" >https://doi.org/10.1080/10556788.2019.1571588</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/10556788.2019.1571588" target="_blank" >10.1080/10556788.2019.1571588</a>
Alternative languages
Result language
angličtina
Original language name
Newton projection with proportioning using iterative linear algebra for model predictive control with long prediction horizon
Original language description
This paper presents an algorithm to solve a sparse Quadratic Programming (QP) problem. The QP problem is suitable for Model Predictive Control (MPC) applications in particular. MPC is a modern multivariable control method which requires the solution to a quadratic programming problem at each sampling instant. The proposed algorithm is an active-set based strategy which uses the proportioning test for the selection of the active-set reduction and expansion while utilizing the sparse nature of the problem by the preconditioned MINRES algorithm to solve the face problem. Numerical experiments illustrate the performance of the algorithm, and the results are compared with the state-of-the-art solvers.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20204 - Robotics and automatic control
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Optimization Methods and Software
ISSN
1055-6788
e-ISSN
1029-4937
Volume of the periodical
34
Issue of the periodical within the volume
5
Country of publishing house
GB - UNITED KINGDOM
Number of pages
24
Pages from-to
1075-1098
UT code for WoS article
000486079100009
EID of the result in the Scopus database
2-s2.0-85061049001