Earticle

초록

영어

This paper addresses an optimal train trajectory planning and tracking problem for automatic train operation (ATO) with consideration of the train model uncertainty and constraints. Based on the discrete linear multi-points train model, an ATO control algorithm is presented to track piecewise reference by using model predictive control with constraints tightening such that the feasibility and robust convergence of this algorithm are guaranteed under the varying running resistance, automatic train protection (ATP) constraint, and train motor physical limits. Specifically, the features of the algorithm are: (i) taking traction and braking force of locomotives and braking force of carriges into account explicitly; (ii) integrating constraints tightening approach into piecewise reference tracking problem to ensure robustness; (iii) combining the optimal planning level and tracking control level together. Finally two case studies are conducted to verify the effectiveness of the algorithm.

목차

Abstract
 1. Introduction
 2. Train Multi-Points Model
  2.1. Notations and Symbols
  2.2. Train Dynamics
 3. Problem Formulation
  3.1. Stage Cost Function
  3.2. Constraints
  3.3. The Maximal Admissible Invariant Set
  3.4. MPC Optimization Problem Formulation
 4. ATO Algorithm Based on CTMPC
 5. Numerical Simulation
  5.1. Case A
  5.2. Case B
 6. Conclusion
 Appendix.
 References

키워드

저자

• Longsheng Wang [ School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China, Architecture and Traffic Engineering College, Guilin University of Electronic Technology, Guilin 541004, China ]
• Hongze Xu [ School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China ]
• Changfu Zou [ Department of Mechanical Engineering, University of Melbourne, Victoria 3010, Australia ]
• Guang Yang [ School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605