张彤

2019年09月06日 14:09 浏览:5789
  姓张彤
  职称:副教授
  专业:控制理论与控制工程 
  邮箱zhang_tong66@126.com
  研究方向:列车网络控制技术、智能控制技术

教育背景
2004.04-2007.07,北京理工大学,控制理论与控制工程,工学博士
2008.04至今,大连交通大学
工作履历

学术兼职

承担科研项目情况
[1] 高速动车组非线性网络系统实时控制方法研究,辽宁省自然科学基金项目,2018.06-2021.06,1/4
[2]高速列车关键系统网络控制方法研究,人工智能四川省重点实验室开放基金项目,2021.09-2023.08,1/4.
[3] 列车重联UIC网关软件设计,企业,3万,2015.04-2017.04, 1/4
[4] 机车车辆安全运用技术研究——高速动车组网络控制系统时延、丢包补偿问题研究,中国铁路总公司,50万,2015.06-2017.12 , 2/7.
奖励与荣誉

学术成果
[1] Switching-Based Sliding Mode Coordination Control for High-Speed Trains Under Coupler Constraints.Nonlinear Dynamics,2025,06. (SCI检索)                                    [2] Forecasting Significant Wave Height Intervals Along China’s Coast Based on Hybrid Modal Decomposition and CNN-BiLSTM. Journal of Marine Science and Engineering,2025,06. (SCI检索)                                                              
[3] Observer-based adaptive memory event-triggered consensus tracking control for high-speed train under DoS attacks. Nonlinear Dynamics,2024,07. (SCI检索)
[4] Fractional Order Nonsingular Terminal Sliding Mode Cooperative Fault-Tolerant Control for High-Speed Trains With Actuator Faults Based on Grey Wolf Optimization. IEEE ACCESS, 2023,06. (SCI检索)
[5] Distributed multiple high-speed trains consensus control based on event-triggered mechanism. Symmetry, 2022, 09. (SCI检索)
[6] Self-Organized Fuzzy Neural Network Nonlinear System Modeling Method Based On Clustering Algorithm. Applied sciences, 2022, 11. (SCI检索)
[7] Distributed Cooperative Sliding Mode Fault-Tolerant Control for Multiple High-Speed Trains Based on Actor-Critic Neural Network[J]. Journal of Mathematics, 2021 (8):1-13. (SCI检索)
[8] 基于改进LS-SVM 算法的列车通信网络时延预测方法. 城市轨道交通研究, 2021,24(01).

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