中国机械工程 ›› 2025, Vol. 36 ›› Issue (11): 2583-2592.DOI: 10.3969/j.issn.1004-132X.2025.11.013

• 机械基础工程 • 上一篇    

磁悬浮列车随机非线性最优控制研究

刘伟渭(), 李阔, 王泓霁, 余玺   

  1. 西南交通大学机械工程学院, 成都, 610031
  • 收稿日期:2024-11-04 出版日期:2025-11-25 发布日期:2025-12-09
  • 通讯作者: 刘伟渭
  • 作者简介:刘伟渭*(通信作者),男,1984年生,副教授。研究方向为轨道车辆和磁悬浮列车系统动力学。 E-mail:liuweiwei1592@163.com
  • 基金资助:
    国家自然科学基金(51875481);四川省科技计划重点研发项目(2023YFN0079)

Research on Stochastic Nonlinear Optimal Control of Maglev Trains

Weiwei LIU(), Kuo LI, Hongji WANG, Xi YU   

  1. School of Mechanical Engineering,Southwest Jiaotong University,Chengdu,610031
  • Received:2024-11-04 Online:2025-11-25 Published:2025-12-09
  • Contact: Weiwei LIU

摘要:

为提高磁悬浮系统的稳定性,考虑气动升力和悬浮力的非线性特征,建立基于Hamilton理论的受控磁悬浮系统随机微分方程。以可靠度最大、平均首次穿越时间最长和最大Lyapunov指数最小为目标,建立最优控制策略的动态规划方程。研究结果表明:考虑PD控制和最优控制联合作用的磁悬浮系统提高了磁悬浮系统的条件可靠性,延长了平均首次穿越时间;经随机稳定化后最大Lyapunov指数始终为负,满足磁悬浮系统平凡解概率为1渐近稳定的条件;经过最优控制后,系统的联合概率密度发生了性态的变化,提高了系统的稳定性;在高斯白噪声强度较低时,以可靠度最大为目标的最优控制策略具有较好的性能指标;以最大Lyapunov指数最小为目标时,仅在某一范围内具有较好的性能指标。通过研究磁悬浮列车的最优控制问题,为提高列车稳定性、延长发生首次穿越失效的时间提供理论依据。

关键词: 磁悬浮列车, 控制策略, 随机激励, 非线性随机动力学

Abstract:

To improve the stability of the maglev systems, the stochastic differential equations for the controlled maglev systems were established based on Hamilton's theory, where the nonlinear characteristics of the aerodynamic lift and levitation forces were taken into account. The dynamic planning equations for an optimal control strategy were developed with the objectives of maximizing the reliability, extending the longest average first-passage time, and minimizing the maximum Lyapunov exponent. The results show that the conditional reliability of the maglev systems may be improved and the average first-passage time prolonged by considering the joint action of PD control and optimal control. Moreover, the maximum Lyapunov exponent is always negative, satisfying the conditions for the trivial solution of the maglev systems to be asymptotically stable with a probability of 1. After optimal control, the joint probability density of the systems undergoes a change in behavior, which improves the system's stability. When the intensity of Gaussian white noise is low, the optimal control strategy for maximum reliability has better performance indicators. However, the strategy for minimum the maximum Lyapunov exponent only exhibits good performance within a certain range. The study of the optimal control problem of the maglev trains provides a theoretical basis for improving the train's stability and prolonging the time until the first-passage failure occurs.

Key words: maglev train, control strategy, random excitation, nonlinear stochastic dynamics

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