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Research on Multi-Objective Real-Time Optimization of Automatic Train Operation(ATO) in Urban Rail Transit 被引量:2

Research on Multi-Objective Real-Time Optimization of Automatic Train Operation(ATO) in Urban Rail Transit
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摘要 The determination and optimization of Automatic Train Operation(ATO) control strategy is one of the most critical technologies for urban rail train operation. The practical ATO optimal control strategy must consider many goals of the train operation, such as safety, accuracy, comfort, energy saving and so on. This paper designs a set of efficient and universal multi-objective control strategy. Firstly, based on the analysis of urban rail transit and its operating environment, the multi-objective optimization model considering all the indexes of train operation is established by using multi-objective optimization theory. Secondly, Non-dominated Sorting Genetic Algorithm II(NSGA-II) is used to solve the model, and the optimal speed curve of train running is generated.Finally, the intelligent controller is designed by the combination of fuzzy controller algorithm and the predictive control algorithm, which can control and optimize the train operation in real time. Then the robustness of the control system can ensure and the requirements for multi-objective in train operation can be satisfied. The determination and optimization of Automatic Train Operation(ATO) control strategy is one of the most critical technologies for urban rail train operation. The practical ATO optimal control strategy must consider many goals of the train operation, such as safety, accuracy, comfort, energy saving and so on. This paper designs a set of efficient and universal multi-objective control strategy. Firstly, based on the analysis of urban rail transit and its operating environment, the multi-objective optimization model considering all the indexes of train operation is established by using multi-objective optimization theory. Secondly, Non-dominated Sorting Genetic Algorithm II(NSGA-II) is used to solve the model, and the optimal speed curve of train running is generated.Finally, the intelligent controller is designed by the combination of fuzzy controller algorithm and the predictive control algorithm, which can control and optimize the train operation in real time. Then the robustness of the control system can ensure and the requirements for multi-objective in train operation can be satisfied.
作者 何彤 熊瑞琦 HE Tong;XIONG Ruiqi(School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, Chin)
出处 《Journal of Shanghai Jiaotong university(Science)》 EI 2018年第2期327-335,共9页 上海交通大学学报(英文版)
关键词 urban rail transit MULTI-OBJECTIVE Automatic Train Operation(ATO) Non-dominated Sorting Genetic Algorithm II(NSGA-II) fuzzy predictive controller urban rail transit, multi-objective, Automatic Train Operation (ATO), Non-dominated Sorting Genetic Algorithm II (NSGA-II), fuzzy predictive controller
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