Research and Simulation on Control Algorithm for Multi-objective Optimization of Urban Rail Train

doi:10.16182/j.issn1004731x.joss.201703016

Abstract

Abstract: According to the characteristics of urban rail train running multiple objective, the multi-objective operation model for urban rail train was established with the energy consumption, punctuality, accurate parking and comfort level as the optimization indexes. Genetic algorithms was used to optimize running multi-objective model of urban rail train, and according to train traction calculation and computer simulation, the train running target curve was obtained. The fuzzy control and PID control algorithm were applied to urban rail train system to establish adaptive fuzzy PID controller and PID control in order to track the target curve. Simulation results show that adaptive fuzzy PID control compared with PID control, the former can better make the train follow the target carve operation, so as to ensure train safety, smooth, punctual operation, at the same time also to ensure the accuracy of a train stopping.

Key words: genetic algorithms, multi-target, traction calculation, target curve, fuzzy PID

CLC Number:

U239.5

Meng Jianjun, Pei Minggao, Wu Fu, Wei Tengzhou, Hao Shuai. Research and Simulation on Control Algorithm for Multi-objective Optimization of Urban Rail Train[J]. Journal of System Simulation, 2017, 29(3): 581-588.

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