Tailored QP Algorithm for Predictive Control with Dynamics Penalty

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00218702" target="_blank" >RIV/68407700:21230/14:00218702 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/MED.2014.6961402" target="_blank" >http://dx.doi.org/10.1109/MED.2014.6961402</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/MED.2014.6961402" target="_blank" >10.1109/MED.2014.6961402</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Tailored QP Algorithm for Predictive Control with Dynamics Penalty

Popis výsledku v původním jazyce

In order to reduce the computational complexity of solving Quadratic Programming (QP), related to linear Model Predictive Control (MPC), a new approximated formulation of the QP with simple bounds is introduced in this paper. This formulation is based onthe idea not to consider model dynamics as a hard constraint but rather modify the objective function of MPC by penalty to capture the violation of model dynamics.The system dynamics is usually uncertain and then it does not make sense to design the control law based on the exact model. Furthermore, the specific sparse structure of the approximated simple bounded QP formulation of the MPC problem is exploited in the new type of combined gradient/Newton step projection algorithm with linear complexity of each iteration with respect to prediction horizon. It is shown by examples that the proposed method is faster on tested problem than other state-of-the-art solvers while retaining a high performance level.

Název v anglickém jazyce

Tailored QP Algorithm for Predictive Control with Dynamics Penalty

Popis výsledku anglicky

In order to reduce the computational complexity of solving Quadratic Programming (QP), related to linear Model Predictive Control (MPC), a new approximated formulation of the QP with simple bounds is introduced in this paper. This formulation is based onthe idea not to consider model dynamics as a hard constraint but rather modify the objective function of MPC by penalty to capture the violation of model dynamics.The system dynamics is usually uncertain and then it does not make sense to design the control law based on the exact model. Furthermore, the specific sparse structure of the approximated simple bounded QP formulation of the MPC problem is exploited in the new type of combined gradient/Newton step projection algorithm with linear complexity of each iteration with respect to prediction horizon. It is shown by examples that the proposed method is faster on tested problem than other state-of-the-art solvers while retaining a high performance level.

Druh

D - Stať ve sborníku

CEP obor

BC - Teorie a systémy řízení

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 22nd Mediterranean Conference on Control & Automation

ISBN

978-1-4799-5900-6

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

384-389

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Palermo

Datum konání akce

16. 6. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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