Abstract
This paper investigates the problem of high speed train operation with special attention to minimizing the discrete constraint conditions between on-board traction network and group signaling equipment. A new discrete fuzzy model for train operation is developed, and its novelty lies in the fact that it optimizes the discrete model using relative degree criterion, which contains two processes of model order identification and model parameters local optimization. Then, we utilize a fuzzy weighted least square method to solve the global optimization problem of model parameters. In the end, simulation experiments have been implemented on the CRH2C-type high speed train, which validates the correctness of the proposed model.
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Acknowledgements
This work is partly supported by the Natural Science Foundation of Jiangxi Province, China under Grant 20132BAB201042, and in part by the research fund of East China Jiaotong University under Grant 12DQ04.
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Zhang, K., An, C. (2018). Discrete Fuzzy Model Optimal Identification Based Approach for High Speed Train Operation. In: Jia, L., Qin, Y., Suo, J., Feng, J., Diao, L., An, M. (eds) Proceedings of the 3rd International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2017. EITRT 2017. Lecture Notes in Electrical Engineering, vol 482. Springer, Singapore. https://doi.org/10.1007/978-981-10-7986-3_96
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DOI: https://doi.org/10.1007/978-981-10-7986-3_96
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