Energy Saving Train Control for Urban Railway Train with Multi-population Genetic Algorithm

被引:14
|
作者
Liu Wei [1 ]
Li Qunzhan [1 ]
Tang Bing [2 ]
机构
[1] Southwest Jiaotong Univ, Sch Elect Engn, Chengdu 610031, Peoples R China
[2] Southwest Jiatong Univ Emei, Emeishan 614202, Peoples R China
关键词
energy saving; minimum principle; multi-model optimization; multi-population genetic algorithm; real-coding;
D O I
10.1109/IFITA.2009.283
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The problem of urban rail train energy saving control with specified running time is a typical multi-constrains, non-linear optimization problem. By applying minimum principle to differential motion model of trains, the energy saving control strategies are obtained. An approach for optimizing problem based on variable-length real matrix coding multi-population genetic algorithm (MPGA) is presented The train running is simulated by a multi-particle simulator considering complicated line conditions and influence of train length. The GA chromosome consisting of a variable-length two dimensional real matrix represents the train control sequence. A variable length operator based on annealing selection is introduced to enhance global search performance. Fitness sharing keeps population's multiplicity. Multi-population parallel search improves convergence rate and evolution stability. The correctness and advancement of the optimization control method have been validated through the simulation platform of train operation.
引用
收藏
页码:58 / +
页数:2
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