Estimator-based H∞ control considering actuator time delay for active double-pantograph in high-speed railways

Xiaobing Lu, Hantao Zhang, Zhigang Liu, Fuchuan Duan, Yang Song, H. Wang

Research output: Contribution to journalArticleScientificpeer-review

3 Citations (Scopus)

Abstract

When two electric multiple units are non-electrically connected together for improving the transport capacity in high-speed railways, double pantographs frequently operate simultaneously to decrease the current capacity on a single pantograph collector. In this case, the contact force between the trailing pantograph and the catenary severely fluctuates due to the wave propagation along the catenary triggered by the leading pantograph. Therefore, this paper proposes two estimator-based H∞ control strategies for active double-pantograph to decrease the contact force fluctuation considering the actuator time delay. To obtain the pantograph states, a robust recursive state estimation method is presented, which can effectively deal with randomly missing measurements. In addition, to overcome parametric uncertainties and non-differentiable actuator time delay, two robust multi-objective H∞ controllers involving linear matrix inequalities are introduced according to whether the time delay can be predetermined or not. The effectiveness and robustness of the control strategies are investigated through implementing a nonlinear double-pantograph-catenary system model. Simulation results show that, for both the leading pantograph and the trailing pantograph, the proposed control strategies can decrease the contact force fluctuation with high efficiency even though the actuator time delay exists.
Original languageEnglish
Pages (from-to)442-457
Number of pages16
JournalJournal of Low Frequency Noise, Vibration and Active Control
Volume40
Issue number1
DOIs
Publication statusPublished - 2019
Externally publishedYes

Keywords

  • Contact force fluctuation
  • active double-pantograph
  • actuator time delay
  • control
  • multi-objective H∞
  • robust recursive state estimation

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