Development of magnetic force modeling equipment for magnetic levitation system

Yang, Ji-Hyuk; Lee, Young‐Sam; Kwon, Oh-Sang

doi:10.1109/iccas.2010.5669947

Cited by 7 publications

(3 citation statements)

References 15 publications

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“…[4][5][6] The controller design and implementation for a magnetic suspension system has been presented by Shiao. 7 An unique method of controller design in levitation system has been highlighted in Matsumura and Yamada 8 and Yang et al 9 Non-linear control design for a magnetic levitation system has been discussed in previous works. [10][11][12] Implementation of sliding mode controller in EM levitation system has been started in early 2000s.…”

Section: Introductionmentioning

confidence: 99%

Design, testing and implementation of a linear state variable feedback controller for providing tracking/regulation of a large platform of a Maglev vehicle

Kundu

Коледов

Stephan

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part I:

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The basic parameters of an electromagnetic levitation systems are resistance of the coil, inductance of the coil, air-gap between magnet and the object, coil current, mass of the object, controller parameters and so on. The levitation systems are highly unstable and strongly non-linear. In real-life applications, these parameters are supposed to vary. A proportional–integral controller for the inner current control loop and a lead compensator for the position control loop have been designed and tested. The performance study under various parametric effects has been investigated broadly. Finally, both the stability for the proposed levitation system has been achieved with a better operating zone using linear state variable feedback controllers. The system dynamic performances have been recorded for variations of physical system parameters. The sensitivity/robustness of the set-up has been studied. This study will give an insight for designing any corrective measures and an overall idea to develop a levitation system.

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Section: Introductionmentioning

confidence: 99%

Design, testing and implementation of a linear state variable feedback controller for providing tracking/regulation of a large platform of a Maglev vehicle

Kundu

Коледов

Stephan

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part I:

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“…Oliveira et al have discussed the digital implementation on levitation prototype for laboratory tests in [8] but no study on validation of analytical and practical is presented. Electromagnetic suspension and levitation technology has been addressed in [9]. However, no study of motion has been discussed.…”

Section: Introductionmentioning

confidence: 99%

Design, analysis, set‐up fabrication, control, and a novel analytical approach of a levitation prototype for a symmetric shaped object

Kundu

2022

Asian Journal of Control

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This paper highlights the design, electromagnetic analysis, system modelling, set-up fabrication, and finally control of an attraction type lab developed levitation prototype. The objectives of this work are parameters' evaluation, for example, force, inductance, and current-air-gap characteristics using a novel analytical model, electromagnetic results, and practical experiments.The FE model has been built using standard packages. A novel permeance function-based approach is developed for the analytical evaluation of parameters. These are verified by actual experiments too with excellent correlation between the sets of results. Agreement between analytical and practical values also show that the modelling is perfect and reliable which further leads to accurate design, fabrication, and implementation of the controller. A simple but reliable controller has been designed, analyzed, and implemented. The performances have been significantly improved. Finally, the steel object has been successfully and steadily levitated in robust condition.

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“…Calculation of the magnetic permanence of the air gap for each pole in a small sampling time weakens any control algorithm; the main reason for this situation is that calculation of the magnetic permanence of the air gap for each pole means that applied force by each pole is being obtained, when a time delay occurs in data acquisition because of the low processing speed of the data acquisition card (and it is commonly accepted that every magnetic levitation application requires very high processing data acquisition speed due to magnetic levitation's highly nonlinear nature [12]), proper actuation signals for coils cannot be produced. As an alternative solution, one may think that using a force sensor may be useful; however, many magnetic levitation systems are very vulnerable in terms of disturbance and, because of this, using a force sensor is not a good engineering implementation; in some cases, the electromagnetic force is generally measured by an additional system consisting of a copy of the levitating object located in a load cell [12,13]. The only remaining reasonable technique for success of controlling magnetic levitation systems is estimating the magnetic force value for each pole.…”

Section: Introductionmentioning

confidence: 99%

Force and torque parameter estimation for a 4-pole hybrid electromagnet by ANFIS hybrid learning algorithm

Atlıhan¹,

Yalçin²,

Erkan³

2017

Turk J Elec Eng & Comp Sci

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Abstract:In this study, a force and torque estimation method based on an adaptive neuro-fuzzy inference system (ANFIS) has been developed to get rid of multiple integral calculations of air gap coefficients that cause time delay for magnetic levitation control applications. During magnetic levitation applications that contain a 4-pole hybrid electromagnet, multiple integral calculations have to be done for obtaining air gap permanence parameters, and these parameters are needed to calculate force and torque parameters that are produced by the poles of the hybrid electromagnet, which means, if time delay occurs for calculation of permanence parameters, actual force and actual torque values that are produced by hybrid electromagnet's poles cannot be exactly known; thus, the advantage of having an exact model of the system gets lost and, as a result, the controller's performance goes down. To address a solution, an ANFIS using a hybrid learning algorithm consisting of backpropagation and least-squares learning methods is proposed to estimate force and torque parameters using training data already obtained using multiple integral calculations before.

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Development of magnetic force modeling equipment for magnetic levitation system

Cited by 7 publications

References 15 publications

Design, testing and implementation of a linear state variable feedback controller for providing tracking/regulation of a large platform of a Maglev vehicle

Design, testing and implementation of a linear state variable feedback controller for providing tracking/regulation of a large platform of a Maglev vehicle

Design, analysis, set‐up fabrication, control, and a novel analytical approach of a levitation prototype for a symmetric shaped object

Force and torque parameter estimation for a 4-pole hybrid electromagnet by ANFIS hybrid learning algorithm

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