Study on iterative learning control in automatic train operation

被引：0

作者：

Wang, Cheng ^{[1
]}

Tang, Tao ^{[1
]}

Luo, Ren-Shi ^{[1
]}

机构：

[1] State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University

来源：

Tiedao Xuebao/Journal of the China Railway Society | 2013年 / 35卷 / 03期

关键词：

ATO; Iterative learning control; Optimization;

D O I：

10.3969/j.issn.1001-8360.2013.03.008

中图分类号：

学科分类号：

摘要：

Study on accurate automatic train stopping holds great practical significance to passenger tansfor at subway stations installed with platform screen doors. In view of the repetitive characteristics of subway trains in stopping the iterative learning control scheme was implemented to adjust the initial state of the trains to eliminate repetitive uncertainty of stop. By solving the differential dynamic train braking model, the system gradient information was obtained and the iterative learning parameters satisfying convergence conditions were found. The multi-object optimization function was defined in consideration of the multiple objectives involved in train stopping. The method was extensively applied in adjustment of multiple various and multiple objectives, which fulfilled the requirements of stopping accuracy, riding comfort and energy saving. The simulation results verified the effectiveness of the method. Finally, future research direction of ATO train stopping was pointed out.

引用

页码：48 / 52

页数：4

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