Maglev systems development status

Eastham, A.R.; Hayes, W.F.

doi:10.1109/62.843

Cited by 27 publications

(7 citation statements)

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“…Holes of university of Virginia in 1937 for the first time, In 1954 this system was utilized by Laurencean and Tournier at ORENA in France for the purpose of aerodynamic testing in wind tunnels [1]. Furthermore, the system is being used in many other applications such as magnetic suspension in high speed trains [2].…”

Section: Introductionmentioning

confidence: 99%

Magnetic levitation control based-on neural network and feedback error learning approach

Aliasghary

Shoorehdeli

Jalilvand

et al. 2008

2008 IEEE 2nd International Power and Energy Conference

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Neural network Based controller is used for controlling a magnetic levitation system. Feedback error learning (FEL) can be regarded as a hybrid control to guarantee stability of control approach. This paper presents simulation of a magnetic levitation system controlled by a FEL neural network and PID controllers. The simulation results demonstrate that this method is more feasible and effective for magnetic levitation system control.

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Section: Introductionmentioning

confidence: 99%

Magnetic levitation control based-on neural network and feedback error learning approach

Aliasghary

Shoorehdeli

Jalilvand

et al. 2008

2008 IEEE 2nd International Power and Energy Conference

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“…Maglev train technology has been widely investigated in the past few decades due to its advantages such as lower noise, less maintenance cost, less exhaust fumes emission and ride comfort [1]. The worldwide interest on the research of maglev train leads to success establishment of several commercial maglev routes and test routes in China, Japan, and Korea [2,3].…”

Section: Introductionmentioning

confidence: 99%

Robust Immersion and Invariance Adaptive Synchronization Control With Disturbance Observer for Maglev Module With Output Constraint

Liu

Zhang

2021

Preprint

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Magnetic levitation module is the key component of maglev train that generates the electromagnet force to bear the weight of the vehicle cabin. In this paper, the mathematical model of the levitation module is built as a two-input and two-output coupled system whose state variables include the vertical linear motion and the rotational motion around the mass center, which fully considers the mechanical coupling and force interference. To alleviate the variation of the module, a framework of robust immersion and invariance (I&I) adaptive synchronization control with disturbance observer is presented for the levitation module. To deal with the bad effects of parametric uncertainties and external disturbances on the system performance, especially on system outputs, we introduce Barrier Lyapunov Function (BLF) into controller to keep the outputs in the prescribed constraints. The robust I&I adaptation law is used to shape the converging procedure of the estimate errors of the parametric uncertainties. An extended disturbance observer is developed to recover the mismatched disturbances of the maglev module simultaneously. The stability analysis shows that all the signals in the closed-loop system are bounded and output constraints are not violated as well. The effectiveness of the proposed scheme is verified by a numerical simulations at last.

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“…Usually, the term "magnetic levitation" can be abbreviated as "maglev" in short. Currently, the applications of maglev include passenger transportation, pallet transportation, wafer transportation, belt conveyors, and transportation systems of bulk materials [4].…”

Section: Introductionmentioning

confidence: 99%

Characterization of Disk-Type Magnetically Levitation Motor

Chen

Fan

Chang

et al. 2007

IECON 2007 - 33rd Annual Conference of the IEEE Industrial Electronics Society

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This paper presents a disk-type magnetic levitation motor (MLM) to provide rotary motion. The proposed MLM offers numerous advantages. First, it can accomplish the levitation force and propulsive force by using only a single power source. Second, with the circular structure, it can provide unlimited traveling distance without the end effect for general characteristics analyses. Third, the stabilization is improved by taking additional mechanical design consideration without using extra set of electromagnet and complicated control. Eventually, a special test facility is designed and implemented for torque test, and the experimental measurements are provided to demonstrate the feasibility of constructing a MLM. Experimental results show that the electrical characteristics of the proposed MLM agree with the theoretical results of a linear induction motor. The measured results can be used to develop a robust controller for the MLM in the future.

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Maglev systems development status

Cited by 27 publications

References 0 publications

Magnetic levitation control based-on neural network and feedback error learning approach

Magnetic levitation control based-on neural network and feedback error learning approach

Robust Immersion and Invariance Adaptive Synchronization Control With Disturbance Observer for Maglev Module With Output Constraint

Characterization of Disk-Type Magnetically Levitation Motor

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