Particle-optimized control for automatic train operation based on sliding mode observer

Author

Mengyang Zhang ; Yao Chen ; Xubin Sun ; Xiaowei Hou ; Hu Cai

Author_Institution

State Key Lab. of Rail Traffic Control & Safety, Beijing Jiaotong Univ., Beijing, China

fYear

2014

fDate

9-10 Oct. 2014

Firstpage

79

Lastpage

84

Abstract

This paper investigates the automatic control problem of high speed train systems under uncertain resistance conditions such as time-varying resistance, unknown aerodynamic drag and wind gust. A sliding mode observer (SMO) based control method is designed for tracking given position-velocity profile precisely. The control method is disturbance rejective that does not rely on specific resistance coefficient. Proposed Method´s parameters have been optimized by particle swarm optimization. The effectiveness of the proposed method is verified via numerical simulations.

Keywords

observers; particle swarm optimisation; rail traffic control; variable structure systems; SMO based control method; automatic train operation; high speed train systems; numerical simulation; particle swarm optimization; particle-optimized control; position-velocity profile; sliding mode observer based control method; time-varying resistance; uncertain resistance conditions; unknown aerodynamic drag; wind gust; Conferences; Control systems; Mathematical model; Noise; Observers; Resistance; Robustness; Automatic Train Operation; Particle Swarm Optimization; Position and Velocity Tracking; Sliding Mode Observer;

fLanguage

English

Publisher

ieee

Conference_Titel

Informative and Cybernetics for Computational Social Systems (ICCSS), 2014 International Conference on

Conference_Location

Qingdao

Print_ISBN

978-1-4799-4753-9

Type

conf

DOI

10.1109/ICCSS.2014.6961820

Filename

6961820