Digitální knihovnaUPCE
 

Fakulta elektrotechniky a informatiky / Faculty of Electrical Engineering and Informatics

Stálý URI pro tuto komunituhttps://hdl.handle.net/10195/3847

Práce obhájené před rokem 2008 jsou uloženy pouze v kolekci Vysokoškolské kvalifikační práce

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20231

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Autor: search.filters.author.Honc, DanielPředmět: search.filters.subject.model predictive controlDatum zahájení: 2020Datum ukončení: 2023

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    Konferenční objektpeer-reviewedpostprintOtevřený přístup
    Application of Model Predictive Controller to Magnetic Levitation
    (IEEE (Institute of Electrical and Electronics Engineers), 2023) Novotný, Aleš; Honc, Daniel
    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.