Title :
Coordinated Iterative Learning Control Schemes for Train Trajectory Tracking With Overspeed Protection
Author :
Heqing Sun ; Zhongsheng Hou ; Dayou Li
Author_Institution :
Adv. Control Syst. Lab., Beijing Jiaotong Univ., Beijing, China
Abstract :
This work embodies the overspeed protection and safe headway control into an iterative learning control (ILC) based train trajectory tracking algorithm to satisfy the high safety requirement of high-speed railways. First, a D-type ILC scheme with overspeed protection is proposed. Then, a corresponding coordinated ILC scheme with multiple trains is studied to keep the safe headway. Finally, the control scheme under traction/braking force constraint is also considered for this proposed ILC-based train trajectory tracking strategy. Rigorous theoretical analysis has shown that the proposed control schemes can guarantee the asymptotic convergence of train speed and position to its desired profiles without requirement of the physical model aside from some mild assumptions on the system. Effectiveness is further evaluated through simulations.
Keywords :
convergence; iterative methods; learning systems; railway safety; traction; trajectory control; D-type ILC scheme; asymptotic convergence; coordinated iterative learning control schemes; high-speed railways; multiple trains; overspeed protection; safe headway control; traction-braking force constraint; train position; train speed; train trajectory tracking algorithm; Convergence; Dynamics; Force; Safety; Trajectory; Uncertainty; Vehicle dynamics; Input constraint; iterative learning control; overspeed protection; safe headway; train control;
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
DOI :
10.1109/TASE.2012.2216261