DocumentCode
43795
Title
Optimal Operation of Heavy-Haul Trains Equipped With Electronically Controlled Pneumatic Brake Systems Using Model Predictive Control Methodology
Author
Lijun Zhang ; Xiangtao Zhuan
Author_Institution
Sch. of Power & Mech. Eng., Wuhan Univ., Wuhan, China
Volume
22
Issue
1
fYear
2014
fDate
Jan. 2014
Firstpage
13
Lastpage
22
Abstract
An optimal control methodology for heavy-haul trains with the objective to optimize the train´s operation in terms of energy consumption, velocity tracking, and operation safety is introduced. Rather than optimize the operation of the train at a specific position, this approach tries to schedule the train during a long period of travel in a model predictive control (MPC) framework; therefore, an effort is made so that the operation strategy of the train is optimal during a track section rather than at a specific position, as is done in existing literature. With this purpose, the cascade mass point model of the train is first simplified and transformed to facilitate the controller design. Then, an optimal controller is presented taking advantage of the MPC concept with the future behavior of the train and all operational constraints considered. Simulations demonstrate the feasibility as well as the advantages of the proposed approach.
Keywords
brakes; control system synthesis; energy consumption; optimal control; pneumatic actuators; predictive control; rail traffic control; railway rolling stock; railway safety; MPC framework; cascade mass point model; controller design; electronically controlled pneumatic brake systems; energy consumption; heavy-haul trains operation; model predictive control methodology; operation safety; operational constraints; optimal control methodology; optimal controller; train scheduling; velocity tracking; Approximation methods; Couplers; Energy consumption; Force; Mathematical model; Optimization; Safety; Heavy-haul trains; model predictive control (MPC); operation optimization;
fLanguage
English
Journal_Title
Control Systems Technology, IEEE Transactions on
Publisher
ieee
ISSN
1063-6536
Type
jour
DOI
10.1109/TCST.2013.2238235
Filename
6450066
Link To Document