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Research on Magnetic Levitation Control Method under Elastic Track Conditions Based on Backstepping Method

Mathematics, ISSN: 2227-7390, Vol: 12, Issue: 13
2024
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Metric Options:   Counts1 Year3 Year

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  • Captures
    1
  • Mentions
    2
    • Blog Mentions
      1
      • Blog
        1
    • News Mentions
      1
      • News
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Recent Findings from National University of Defense Technology Highlight Research in Mathematics (Research on Magnetic Levitation Control Method under Elastic Track Conditions Based on Backstepping Method)

2024 JUL 22 (NewsRx) -- By a News Reporter-Staff News Editor at Math Daily News -- New research on mathematics is the subject of a

Article Description

The vehicle–guideway coupled self-excited vibration of maglev systems is a common control instability problem in maglev traffic while the train is suspended above flexible girders, and it seriously affects the suspension stability of maglev vehicles. In order to solve this problem, a nonlinear dynamic model of a single-point maglev system with elastic track is established in this paper, and a new and more stable adaptive backstepping control method combined with magnetic flux feedback is designed. In order to verify the control effect of the designed control method, a maglev vehicle–guideway coupled experimental platform with elastic track is built, and experimental verifications under rigid and elastic conditions are carried out. The results show that, compared with the state feedback controller based on the feedback linearization controller, the adaptive backstepping control law proposed in this paper can achieve stable suspension under extremely low track stiffness, and that it shows good stability and anti-interference abilities under elastic conditions. This work has an important meaning regarding its potential to benefit the advancement of commercial maglev lines, which may significantly enhance the stability of the maglev system and reduce the cost of guideway construction.

Bibliographic Details

Pengxiang Zhu; Te Zhang; Danfeng Zhou; Jie Li; Yuxin Jin; Qicai Li

MDPI AG

Computer Science; Mathematics; Engineering

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