Online Regulation of High Speed Train Trajectory Control Based on T-S Fuzzy Bilinear Model

Multiobjective operation optimization for high-speed trains (HSTs) is hardly implemented by manual operation due to the increasing operational complexity and environmental uncertainties. In this paper, a T-S fuzzy bilinear model is established based on the nonlinear dynamics of the HST. A new adaptive predictive control approach based on the T-S fuzzy bilinear model of HST control is proposed with consideration of security, punctuality, and energy efficiency. In view of the model's adaptability and the approach's real-time performance, a lazy learning algorithm is used to adjust the parameters of the model and controller online while the model prediction error exceeds a given threshold. Simulation results based on the real HST running data show that the proposed approach contributes a significant improvement in HSTs' tracking precision and energy efficiency.


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  • Accession Number: 01603699
  • Record Type: Publication
  • Files: TLIB, TRIS
  • Created Date: May 31 2016 1:42PM