Sampled Data Sliding Mode Control of Magnetic Levitation System Using Extended Kalman Filter Estimator

Naz, Neelma; Malik, Mohammad Bilal; Zaheer, Asim

doi:10.1109/eurosim.2013.47

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…W literaturze można znaleźć wiele odmian metod estymacji, które wciąż są powszechnie rozwijane do różnych zastosowań. W pracy [19], na obiekcie MLS, przy dostępie do pomiaru wyłącznie położenia, odtworzono pełny stan realizując algorytm EKF. Umożliwiło to zastosowanie regulatora bazującego na sprzężeniu od stanu.…”

Section: äˁǜɂʁ ǘɂʁƭʊɡɂȭƞˁǖŭƌ˿ƕ àǔǘɂȧřǖ àʁɂǜƭǘƙ ȧǔǘɂǚřǖɩȧʁɂǜƭǘźǔȭǜƭʁǔřɩɡǚunclassified

Control of the Magnetic Levitation System in Conditions of Stochastic Disturbances

Mrotek¹,

Szymankiewicz²,

Michalski³

et al. 2022

PAR

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This paper presents the possibility of reducing impact of stochastic disturbances on the quality of control by implementation of state estimation using the extended Kalman filter algorithm. Experiments were carried out on the Inteco magnetic levitation laboratory system, which mathematical model is nonlinear. A control method with the use of a state vector and a pole placement algorithm was adopted for the model which was linearized at the selected working point. For different levels of noise in the measurement signal, the operation of the system with a feedback from the measured and estimated state was tested. In order to assess the regulation, the quality of the algorithm was verified for both implementations of the feedback. The obtained time plots of each state variable were compared and the calculated integral quality indices, based on the control error, were compared. The quality of the estimation was assessed on the basis of the following mean square error and based on the errors between estimation and measurements indices. The controller was synthesized on thebasis of the continuous model, and then its discrete form was numerically implement as the extender Kalman filter algorithm. The executive blocks were synchronized with the selected sampling period. The results of the performed research allow to conclude about the advantage of control in the system in which the information about the state vector from the estimation is taken, in comparison with the direct feedback without Kalman filtering.

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Section: äˁǜɂʁ ǘɂʁƭʊɡɂȭƞˁǖŭƌ˿ƕ àǔǘɂȧřǖ àʁɂǜƭǘƙ ȧǔǘɂǚřǖɩȧʁɂǜƭǘźǔȭǜƭʁǔřɩɡǚunclassified

Control of the Magnetic Levitation System in Conditions of Stochastic Disturbances

Mrotek¹,

Szymankiewicz²,

Michalski³

et al. 2022

PAR

View full text Add to dashboard Cite

show abstract

Real time implementation of feedback linearizing controllers for magnetic levitation system

Naz

Malik

2013

2013 IEEE Conference on Systems, Process &Amp; Control (ICSPC)

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Sampled Data Sliding Mode Control of Magnetic Levitation System Using Extended Kalman Filter Estimator

Cited by 2 publications

References 11 publications

Control of the Magnetic Levitation System in Conditions of Stochastic Disturbances

Control of the Magnetic Levitation System in Conditions of Stochastic Disturbances

Real time implementation of feedback linearizing controllers for magnetic levitation system

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