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author:

Zhang, Louyue (Zhang, Louyue.) [1] | Xiao, Gaoxi (Xiao, Gaoxi.) [2] | Zhai, Chao (Zhai, Chao.) [3] | Zhang, Hehong (Zhang, Hehong.) [4]

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EI

Abstract:

The levitation control system is a critical subsystem in maglev trains, ensuring stable levitation of the train on the guideway. Achieving stable levitation requires providing the system with accurate levitation gap and corresponding velocity data while minimizing phase lag. This work proposes an enhanced tracking differentiator (TD) to reduce phase lag in both filtering and differentiation of input signals with varying noise levels. The improved performance is achieved by incorporating system damping and an amplitude factor into the control algorithm used to design the differentiator. Theoretical analysis guarantees the convergence of the proposed algorithm. Simulations and experiments conducted on the levitation gap data demonstrate the superior performance of the proposed TD in reducing phase lag for both filtered and differentiated signals. Furthermore, experimental results highlight the improved performance of the feedback controller when employing the proposed TD. © 2024 The Author(s). IET Control Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

Keyword:

Control nonlinearities Damping Electromagnetic induction Guideways Levitation melting Light rail transit Magnetic levitation Magnetic levitation vehicles Navigation Phase noise Railroad transportation

Community:

  • [ 1 ] [Zhang, Louyue]School of Energy and Power Engineering, Beihang University, Beijing, China
  • [ 2 ] [Xiao, Gaoxi]School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore
  • [ 3 ] [Zhai, Chao]School of Automation, China University of Geosciences, Wuhan, China
  • [ 4 ] [Zhang, Hehong]College of Computer and Data Science, Fuzhou University, Fuzhou, China

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Source :

IET Control Theory and Applications

ISSN: 1751-8644

Year: 2025

Issue: 1

Volume: 19

2 . 2 0 0

JCR@2023

Cited Count:

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SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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