Optimization of a Real-Time Stabilization System for the MIMO Nonlinear MagLev Platform

Zavadskiy, Sergey; Verkhoturov, M. S.; Golovkina, Anna; Ovsyannikov, Dmitri; Kukhtin, V.; Shatil, N.; Belov, Andrei A.

doi:10.1007/978-3-030-87966-2_31

Cited by 1 publication

(1 citation statement)

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“…The attraction between the levitation core electromagnet and the ferromagnetic rails is used to maintain the levitation stability so that the carriages can be suspended in the air. [5][6][7] The magnetic levitation control system is the core part of the maglev train, and its dynamic performance determines the comfort and safety of the train system because it is controlled by strong non-linear electromagnetic forces, so the optimization of the performance of the levitation control system is necessary.…”

Section: Introductionmentioning

confidence: 99%

Parameter optimization of electromagnetic suspension-type maglev train control system based on multi-objective grey wolf non-dominated sorting hybrid algorithm-Ⅱ hybrid algorithm

Wang,

Zeng,

Liu

et al. 2023

Journal of Low Frequency Noise, Vibration and Active Control

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This paper presents a novel hybrid algorithm based on CMOGWO-ADNSGA-II to solve the vibration stability problem during the operation of a EMS-type maglev train dynamics model subjected to strong non-linear magnetic buoyancy. The proposed algorithm optimizes the control system parameters of EMS-type maglev train suspensions by combining an improved multi-objective chaotic grey wolf algorithm (CMOGWO) with an improved non-dominated Sorting genetic algorithm-II (ADNSGA-II) to enhance the search capability of the algorithm and ensure population diversity. The efficacy of the algorithm is demonstrated by applying it to the EMS-type maglev train suspension frame control system to find the optimal control parameters. Experimental results show that the system with the optimal parameters applied significantly reduces the suspension gap amplitude and the corresponding standard deviation, as well as the vertical acceleration amplitude and the corresponding standard deviation during operation. The proposed algorithm provides a good solution for EMS-type maglev train suspension vibration control, which can improve its performance and safety.

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Section: Introductionmentioning

confidence: 99%