Application of Model Predictive Controller to Magnetic Levitation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F23%3A39920927" target="_blank" >RIV/00216275:25530/23:39920927 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/10217631" target="_blank" >https://ieeexplore.ieee.org/document/10217631</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/PC58330.2023.10217631" target="_blank" >10.1109/PC58330.2023.10217631</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Application of Model Predictive Controller to Magnetic Levitation

Popis výsledku v původním jazyce

Model Predictive Control (MPC) is an advanced process control method that is widely used for controlling both linear and under some modifications for non-linear systems. The aim of this work is to show a way how to apply MPC to a non-linear Magnetic Levitation System (MLS) and its capability of stabilization and closed-loop performance. This work is a continuation of the previous article where the laboratory plant CE 152 MLS was identified, and a non-linear model was designed. This paper proposes a control circuit consisting of linearized discretized non-linear MLS model, Extended Kalman Filter (EKF) algorithm for state estimation and linear MPC. The results are verified in simulation and real-world experiment.

Název v anglickém jazyce

Application of Model Predictive Controller to Magnetic Levitation

Popis výsledku anglicky

Model Predictive Control (MPC) is an advanced process control method that is widely used for controlling both linear and under some modifications for non-linear systems. The aim of this work is to show a way how to apply MPC to a non-linear Magnetic Levitation System (MLS) and its capability of stabilization and closed-loop performance. This work is a continuation of the previous article where the laboratory plant CE 152 MLS was identified, and a non-linear model was designed. This paper proposes a control circuit consisting of linearized discretized non-linear MLS model, Extended Kalman Filter (EKF) algorithm for state estimation and linear MPC. The results are verified in simulation and real-world experiment.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název statě ve sborníku

Process control 23 : proceedings of the 2023 24th international conference on process control (PC)

ISBN

979-8-3503-4762-3

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

90-95

Název nakladatele

IEEE (Institute of Electrical and Electronics Engineers)

Místo vydání

New York

Místo konání akce

Štrbské Pleso

Datum konání akce

6. 6. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001058530100016