High-speed train trajectory tracking based on event-triggered predictive control

The open operating environment of high-speed trains exposes them to disturbances from external resistances, which are difficult to characterize through modeling. To address this issue, this paper investigates a train model predictive tracking control (TMPC) strategy, with safety, ride comfort and pu...

Full description

Saved in:
Bibliographic Details
Published in机车电传动 pp. 148 - 154
Main Authors JIN Wenbin, ZHANG Jiahui, YAO Bailing, SUN Pengfei, WANG Qingyuan
Format Journal Article
LanguageChinese
Published Editorial Department of Electric Drive for Locomotives 01.07.2024
Subjects
automatic train operation
event-triggered control
high-speed train
model predictive control
trajectory tracking
Online AccessGet full text
ISSN1000-128X

Cover

More Information
Summary:The open operating environment of high-speed trains exposes them to disturbances from external resistances, which are difficult to characterize through modeling. To address this issue, this paper investigates a train model predictive tracking control (TMPC) strategy, with safety, ride comfort and punctuality as the tracking objectives. Firstly, a multi-objective predictive control model with constraints was constructed for high-speed trains, and the Tube invariant set of the system was calculated to tightly constrain train states and control forces. On this basis, in order to reduce the computational workload for solving the optimal control online, a dynamic event-triggered Tube model predictive control (DETMPC) strategy was designed, enabling the optimal control sequence to be solved only when the triggering conditions were satisfied. Furthermore, simulation verification was carried out using Shanghai urban trains running on real tracks. The results show that the control strategy proposed in this paper not o
ISSN:1000-128X