Newton projection with proportioning using iterative linear algebra for model predictive control with long prediction horizon

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Newton projection with proportioning using iterative linear algebra for model predictive control with long prediction horizon

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Newton projection with proportioning using iterative linear algebra for model predictive control with long prediction horizon

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Optimization Methods and Software

ISSN

1055-6788

e-ISSN

1029-4937

Svazek periodika

34

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

24

Strana od-do

1075-1098

Kód UT WoS článku

000486079100009

EID výsledku v databázi Scopus

2-s2.0-85061049001