Magnetic Levitation – Modelling, Identification and Open Loop Verification Article Swipe

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Daniel Honc , Eleonora Riva Sanseverino ·

YOU? · · 2019 · Open Access · · DOI: https://doi.org/10.14311/tee.2019.1.013

The paper describes a procedure using the first principle modelling and experimental identification of the Magnetic Levitation Model CE 152. It is a modified version of the paper [1]. The difference is that the identification and verification is done in open loop and constraints logic is added in the current paper. The author optimized and simplified dynamic model to a minimum to what is needed to characterize given system for the simulation and control design purposes. Only few open-loop experiments are needed to estimate the unknown parameters. Model quality is verified in open loop where the real and simulated data are compared. The model can serve as a simulation model for some standard control algorithms or as a process model for advanced control method design.

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Open-loop controller Magnetic levitation Identification (biology) Computer science Control theory (sociology) Loop (graph theory) Process (computing) Levitation Control (management) Control engineering Closed loop Engineering Mathematics Magnet Artificial intelligence Combinatorics Operating system Mechanical engineering Biology Botany

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Type: article
Language: en
Landing Page: https://doi.org/10.14311/tee.2019.1.013
PDF: https://ojs.cvut.cz/ojs/index.php/TEE/article/download/6324/5474
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Cited By: 4
References: 19
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DOI: https://doi.org/10.14311/tee.2019.1.013

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Title: Magnetic Levitation – Modelling, Identification and Open Loop Verification

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Language: en

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Publication year: 2019

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Publication date: 2019-04-01

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Authors: Daniel Honc, Eleonora Riva Sanseverino

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Landing page: https://doi.org/10.14311/tee.2019.1.013

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Concepts: Open-loop controller, Magnetic levitation, Identification (biology), Computer science, Control theory (sociology), Loop (graph theory), Process (computing), Levitation, Control (management), Control engineering, Closed loop, Engineering, Mathematics, Magnet, Artificial intelligence, Combinatorics, Operating system, Mechanical engineering, Biology, Botany

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Cited by: 4

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Citations by year (recent): 2024: 1, 2021: 1, 2019: 2

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citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	False