The research of fuzzy predicting and its application in train's automatic control

Feng, Xiaoyun; Jia, Jing; Li, Zhi

doi:10.1109/iwads.2000.880890

Cited by 5 publications

(1 citation statement)

References 3 publications

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“…In this article voltage control method is used for traction motor rev control [4]. In this method the average voltage is altered by changing the ignition angle of thyristor, although to decrease the simulation time a multi-switch with various voltages is used.…”

Section: Modeling the Train And Automatic Train Operation Systemmentioning

confidence: 99%

Improvement of Automatic Train Operation Using Enhanced Predictive Fuzzy Control Method

Sandidzadeh¹,

Shamszadeh²

2012

Reliability and Safety in Railway

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Section: Modeling the Train And Automatic Train Operation Systemmentioning

confidence: 99%

Improvement of Automatic Train Operation Using Enhanced Predictive Fuzzy Control Method

Sandidzadeh¹,

Shamszadeh²

2012

Reliability and Safety in Railway

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Study on Optimization of automatic train operation based on Grey genetic algorithm

Gao

2019

J. Phys.: Conf. Ser.

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The speed controller is the kernel module of Automatic Train Operation system, and is also a key core technology of the intelligent high-speed train. The research of the intelligent speed controller of ATO system is of great significance for automatic high-speed train operation. Through the analysis of the principle and function of CTCS-3 system, the scheme of adding the speed controller of ATO system in CTCS-3 system was proposed. The connection way between the speed controller of ATO system and ground equipment was designed to realize information interaction. The model of speed controller of ATO system for high-speed trains which is researched by grey system theory was used for prediction and decision making. In the grey prediction module, the metabolic GM (1,1) model was established, and the optimal strategy was generated by the multi-objective intelligent weighted grey target decision. Finally, a reasonable control strategy of train automatic operation was obtained. The optimal control strategy was got by using genetic algorithm. Designing software for the simulation test, the simulation results show that the method achieves automatic high-speed train operation under the CTCS-3+ATO system through the actual line data, and the efficiency of train operation, the energy saving index and all the performance indexes of the train were improved.

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The simulation research for the ATO model based on fussy predictive control

Zhu

Feng

et al.

Proceedings Autonomous Decentralized Systems, 2005. ISADS 2005.

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The research of fuzzy predicting and its application in train's automatic control

Cited by 5 publications

References 3 publications

Improvement of Automatic Train Operation Using Enhanced Predictive Fuzzy Control Method

Improvement of Automatic Train Operation Using Enhanced Predictive Fuzzy Control Method

Study on Optimization of automatic train operation based on Grey genetic algorithm

The simulation research for the ATO model based on fussy predictive control

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