| 交通工程、土木工程 |
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| 跟踪性能约束下的非线性列车无模型控制 |
宋家成( ),张雅楠 |
| 西北农林科技大学 机械与电子工程学院,陕西 杨凌 712100 |
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| Model-free control of nonlinear train under tracking performance constraint |
Jiacheng SONG( ),Yanan ZHANG |
| College of Mechanical and Electronic Engineering, Northwest A & F University, Yangling 712100, China |
| 1 |
张淼, 张琦, 刘文韬, 等 一种基于策略梯度强化学习的列车智能控制方法[J]. 铁道学报, 2020, 42 (1): 69- 75 ZHANG Miao, ZHANG Qi, LIU Wentao, et al A policy-based reinforcement learning algorithm for intelligent train control[J]. Journal of the China Railway Society, 2020, 42 (1): 69- 75
doi: 10.3969/j.issn.1001-8360.2020.01.010
|
| 2 |
陆源源, 王慧, 宋春跃 考虑列车混行的运行-调度一体化优化方法[J]. 浙江大学学报: 工学版, 2018, 52 (1): 106- 116 LU Yuanyuan, WANG Hui, SONG Chunyue Integrated optimization method of scheduling and control in express/slow train[J]. Journal of Zhejiang University: Engineering Science, 2018, 52 (1): 106- 116
|
| 3 |
张鑫, 祝子钧, 陈凯生 基于自适应终端滑模的高速列车迭代学习速度控制[J]. 铁道学报, 2024, 46 (9): 76- 84 ZHANG Xin, ZHU Zijun, CHEN Kaisheng Adaptive terminal sliding mode based iterative learning speed control for high-speed trains[J]. Journal of the China Railway Society, 2024, 46 (9): 76- 84
doi: 10.3969/j.issn.1001-8360.2024.09.009
|
| 4 |
岳丽丽, 王一栋, 肖宝弟, 等 城轨列车自动驾驶积分反步线性自抗扰控制[J]. 湖南大学学报: 自然科学版, 2024, 51 (8): 78- 90 YUE Lili, WANG Yidong, XIAO Baodi, et al Integral back-stepping linear active disturbance rejection control for automatic operation of urban rail trains[J]. Journal of Hunan University: Natural Sciences, 2024, 51 (8): 78- 90
|
| 5 |
CAO Y, WEN J, MA L Tracking and collision avoidance of virtual coupling train control system[J]. Alexandria Engineering Journal, 2021, 60 (2): 2115- 2125
doi: 10.1016/j.aej.2020.12.010
|
| 6 |
WEI G, ZHU S, WANG Y Energy-efficient automatic train operation for high-speed railways: considering discrete notches and neutral sections[J]. Transportation Research Part C: Emerging Technologies, 2022, 145: 103884
doi: 10.1016/j.trc.2022.103884
|
| 7 |
LIU Y, ZHOU Y, SU S, et al An analytical optimal control approach for virtually coupled high-speed trains with local and string stability[J]. Transportation Research Part C: Emerging Technologies, 2021, 125: 102886
doi: 10.1016/j.trc.2020.102886
|
| 8 |
HE J, YANG X, ZHANG C, et al Tracking control via sliding mode for heavy-haul trains with input saturation[J]. Measurement and Control, 2020, 53 (9): 1720- 1729
|
| 9 |
ZHAO H, DAI X, ZHANG Q, et al Robust event-triggered model predictive control for multiple high-speed trains with switching topologies[J]. IEEE Transactions on Vehicular Technology, 2020, 69 (5): 4700- 4710
doi: 10.1109/TVT.2020.2974979
|
| 10 |
XIAO Z, WANG Q, SUN P, et al Modeling and energy-optimal control for high-speed trains[J]. IEEE Transactions on Transportation Electrification, 2020, 6 (2): 797- 807
doi: 10.1109/TTE.2020.2983855
|
| 11 |
ZHANG Z, CHEN Z, FANG W Asymptotical cooperative cruise fault tolerant control for multiple high-speed trains with state constraints[J]. IFAC-PapersOnLine, 2023, 56 (2): 856- 861
|
| 12 |
YU W, HUANG D, WANG Q, et al Distributed event-triggered iterative learning control for multiple high-speed trains with switching topologies: a data-driven approach[J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24 (10): 818- 829
|
| 13 |
LUO M, KE Q, LI J Research on automatic braking and traction control of high-speed train based on neural network[J]. Journal of Physics: Conference Series, 2021, 1952 (3): 032048
doi: 10.1088/1742-6596/1952/3/032048
|
| 14 |
XUN J, CHEN M, LIU Y, et al An overspeed protection mechanism for virtual coupling in railway[J]. IEEE Access, 2020, 8: 187400- 187410
doi: 10.1109/ACCESS.2020.3029147
|
| 15 |
SU S, LIU W, ZHU Q, et al A cooperative collision-avoidance control methodology for virtual coupling trains[J]. Accident Analysis and Prevention, 2022, 173: 106703
doi: 10.1016/j.aap.2022.106703
|
| 16 |
YUAN H, HUANG D, LI X Adaptive speed tracking control for high speed trains under stochastic operation environments[J]. Automatica, 2023, 147: 110674
doi: 10.1016/j.automatica.2022.110674
|
| 17 |
GAO S, WEN J, SONG H, et al Fuzzy adaptive automatic train operation control with protection constraints: a residual nonlinearity approximation-based approach[J]. Engineering Applications of Artificial Intelligence, 2020, 96 (2): 103986
|
| 18 |
FELEZ J, KIM Y, BORRELLI F A model predictive control approach for virtual coupling in railways[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 20 (7): 2728- 2739
doi: 10.1109/TITS.2019.2914910
|
| 19 |
DONG H, LIN X, GAO S, et al Neural networks-based sliding mode fault-tolerant control for high-speed trains with bounded parameters and actuator faults[J]. IEEE Transactions on Vehicular Technology, 2020, 69 (2): 1353- 1362
doi: 10.1109/TVT.2019.2961409
|
| 20 |
GAO S, HOU Y, DONG H, et al High-speed trains automatic operation with protection constraints: a resilient nonlinear gain-based feedback control approach[J]. IEEE/CAA Journal of Automatica Sinica, 2019, 6 (4): 992- 999
doi: 10.1109/JAS.2019.1911582
|
| 21 |
GAO S, LI M, ZHENG Y, et al Fuzzy adaptive protective control for high-speed trains: an outstretched error feedback approach[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23 (10): 966- 975
|
| 22 |
ILCHMANN A, RYAN E P, SANGWIN C J Systems of controlled functional differential equations and adaptive tracking[J]. SIAM Journal on Control and Optimization, 2002, 40 (6): 1746- 1764
doi: 10.1137/S0363012900379704
|
| 23 |
ILCHMANN A, RYAN E P, SANGWIN C J Tracking with prescribed transient behaviour[J]. ESAIM Control, Optimisation and Calculus of Variations, 2002, 7 (7): 471- 493
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