殷辰堃

副教授
  • 副系主任，副所长
  • 研究生
  • 博士
  • chkyin@bjtu.edu.cn
  • 北京交通大学自动化与智能学院九教西501室先进控制系统研究所

教育背景

    2006/09-2011/06，北京交通大学，电子信息工程学院，交通信息工程及控制专业，工学博士，导师：侯忠生
    2008/08-2009/09，新加坡国立大学，Electrical and Computer Engineering Department，国家公派联合培养博士生，导师：Jian-Xin Xu
    2003/09-2006/06，山东大学，数学与系统科学学院，运筹学与控制论专业，理学硕士，导师：吴臻
    1999/09-2003/06，西安交通大学，理学院，信息与计算科学专业，理学和金融学双学士

工作经历

        2011年7月-2013年12月，在北京交通大学电子信息工程学院任教。历任讲师、副教授。硕导。

        2024至今，北京交通大学自动化与智能学院，副教授，博导。

研究方向

  • 控制理论与控制工程
  • 控制工程
  • 人工智能
  • 新一代电子信息技术

招生专业

  • 控制科学与工程博士
  • 控制科学与工程硕士
  • 控制工程硕士
  • 人工智能硕士
  • 新一代电子信息技术（含量子技术等）硕士

科研项目

  1. 国家自然科学基金"面上项目":迭代变化参数不确定系统的数据驱动迭代学习控制方法研究,2023-2026,主持
  2. 国家自然科学基金"青年项目":非严格重复连续时间系统的迭代学习控制方法及应用研究,2015-2017,主持
  3. 基本科研业务费:受限迭代学习控制及其在列车运行控制中的应用,2017-2018,主持
  4. 基本科研业务费:基于优化理论的迭代学习控制器设计及鲁棒性研究,2012-2014,主持
  5. 中国船舶工业系统工程研究院:AIS目标航迹建航与滤波技术研究,2014-2015,主持
  6. 北京市信息资源管理中心:2012年资源专项分包之绿色出行主题目录信息共享应用,2012-2013,主持
  7. 国家自然科学基金“重点项目”:数据驱动的地铁无人智能驾驶基础理论与技术,2020-2024,参加
  8. 国家自然科学基金“重点项目”:大数据环境下的复杂城市交通系统预测与控制,2015-2019,参加
  9. 国家自然科学基金“重大国际合作项目”:广义迭代学习控制理论及在高速列车运行控制中的应用,2012-2016,参加
  10. 国家自然科学基金“面上项目”:全自动运行系统中基于自主控制的列车节能运行与优化,2021-2024,参加
  11. 国家自然科学基金“面上项目”:数据驱动的高速列车学习自适应容错控制理论与应用,2021-2024,参加
  12. 国家自然科学基金“面上项目”:高阶内模学习控制理论及在快速路交通控制中的应用,2008-2010,参加
  13. 国家自然科学基金“主任基金项目”:数据驱动的自适应迭代学习控制及其在交通系统中的应用,2011-2011,参加
  14. 北京市自然科学基金"丰台轨道交通前沿研究联合基金":基于车网协同的城轨列车群节能运行动态优化方法,2023-2026,参加
  15. 北京市自然科学基金"交控科技轨道交通联合基金项目":城市地铁列车运行的数据驱动控制与滤波方法,2017-2019,参加
  16. 基本科研业务费“重大项目”:智能高速铁路系统理论方法体系研究,2018-2021,参加
  17. 基本科研业务费“重点项目”:面向磁悬浮列车的CPS 智能协同容错控制研究,2022-2025,参加
  18. 基本科研业务费:城市路网宏观区域划分与边界交通流混杂控制方法研究,2016-2018,参加
  19. 中国国家铁路集团有限公司:技术作业站站区一体化平行调度系统关键技术研究,2022-2024,参加
  20. 招商新智:路网运行监测管理时空数据处理技术及智能分析算法,2022,参加
  21. 北京机电工程研究所:水下仿生机器人无模型控制技术研究,2018-2019,参加
  22. 北京航天自动控制研究所:基于数据驱动的飞行控制技术研究,2017-2018,参加
  23. 中国航天系统工程有限公司:快速路入口匝道控制系统开发,2012-2013,参加
  24. 中国航天系统工程有限公司:城市道路交通调查、布控与公交应急系统设计与布设,2013-2013,参加

教学工作

    本科：运筹学，智能装备与系统专业综合实验，自动化专业毕业实习，自动化专业综合实验，Matlab基础与应用。
    研究生：最优化理论、方法及应用，道路交通控制工程，

论文/期刊

  1. Chenkun Yin, Jian-Xin Xu and Zhongsheng Hou, “Iterative learning control design with high-order internal model for nonlinear systems,” in Proceedings of the 48th IEEE Conference on Decision and Control held jointly with the 2009 28th Chinese Control Conference, Shanghai, China, Dec. 2009. pp. 434-439
  2. Chenkun Yin, Jian-Xin Xu and Zhongsheng Hou, “An ILC scheme for a class of nonlinear systems with time-varying parameters subject to second-order internal model,” in Proceedings of the 48th IEEE Conference on Decision and Control held jointly with the 2009 28th Chinese Control Conference, Shanghai, China, Dec. 2009. pp. 452-457
  3. Chenkun Yin, and Zhongsheng Hou, “Adaptive iterative learning control for a class of iteration-varying nonlinear systems with known periodicity,” in 2009 International Conference on Test and Measurement, Shenzhen, China, Dec. 2009, pp.433-437
  4. Chenkun Yin, Jian-Xin Xu and Zhongsheng Hou, “On iterative learning control design for tracking iteration-varying trajectories with high-order internal model,” Journal of Control Theory and Applications, special issue in honor of the 60th Birthday of Professor Frank L. Lewis, Vol.8, no.3, pp.309-316, 2010
  5. 殷辰堃, 许建新, 侯忠生, “两种基于二阶内模的迭代学习控制器设计,” 北京交通大学学报, Vol.5, no.34, pp.105-110, 2010
  6. Chenkun Yin, Jian-Xin Xu and Zhongsheng Hou, “A high-order internal model based iterative learning control scheme for nonlinear systems with time-iteration-varying parameters,” IEEE Transactions on Automatic Control, Vol.55, no.11, pp.2665-2670, 2010
  7. Chenkun Yin, Jian-Xin Xu and Zhongsheng Hou, “Corrections to “A high-order internal model based iterative learning control scheme for nonlinear systems with time-iteration-varying parameters”,” IEEE Transactions on Automatic Control, Vol.56, no.1, pp.2350, 2011
  8. Chenkun Yin, Jian-Xin Xu and Zhongsheng Hou, “An ILC scheme for a class of nonlinear continuous-time systems with time-iteration-varying parameters subject to second-order internal model,” Asian Journal of Control, special issue on Iterative Learning Control, Vol.13, no.1, pp.126-135, 2011
  9. Zhongsheng Hou, Yi Wang, Chenkun Yin and Tao Tang, “Terminal iterative learning control based station stop control of a train,” International Journal of Control, special issue on Iterative Learning Control, vol.84, no.7, pp.1263-1274, 2011
  10. Wen Yang, Chenkun Yin and Zhongsheng Hou, “A novel energy efficient operation strategy for a train based on model-free adaptive predictive control,” in Proceedings of the 31st Chinese Control Conference, Heifei, China, July 2012, pp. 7286-7291
  11. Zhenxuan Li, Chenkun Yin, Shangtai Jin and Zhongsheng Hou, “Iterative learning control based automatic train operation with iteration-varying parameter,” in Proceedings of the10th IEEE International Conference on Control and Automation (ICCA), Hangzhou, China, June 2013, pp. 51-56
  12. Shida Liu, Zhongsheng Hou and Chenkun Yin, “Data-driven modeling for fixed-bed intermittent gasification processes by enhanced lazy learning incorporating with relevance vector machine,” in Proceedings of the 11th IEEE International Conference on Control and Automation (ICCA), Taichung, Taiwan, June 2014, pp. 1019-1024
  13. Shida Liu, Zhongsheng Hou and Chenkun Yin, “Data driven modeling for UGI gasification process via a variable structure genetic BP neural network,” in Proceedings of 2014 International Joint Conference on Neural Networks (IJCNN), Beijing, China, July 2014, pp. 1071-1078
  14. Zhenxuan Li, Zhongsheng Hou and Chenkun Yin, “Iterative learning control for train trajectory tracking under speed constrains with iteration-varying parameter,” Transactions of the Institute of Measurement and Control, Vol.37 , no.4, pp.485-493, 2015
  15. 王明月, 殷辰堃, “基于合作博弈的道路交叉口信号配时优化策略”, 第27届中国控制与决策会议 (2015 CCDC), Qingdao, China, March 2015, pp.5148-5153
  16. Zhongsheng Hou, Qiongxia Yu, Jian-Xin Xu and Chenkun Yin, “A simultaneous iterative learning control and dynamic modeling approach for a class of nonlinear systems”, in Proceedings of the 17th IFAC Symposium on System Identification (SYSID 2015), Beijing, China, Oct 2015, pp.368-373
  17. Ruikun Zhang, Zhongsheng Hou, Honghai Ji and Chenkun Yin, “Adaptive iterative learning control for a class of nonlinearly parameterized systems with input saturations,” International Journal of Systems Sciences, Vol.47, no.5, pp.1084-1094, 2016
  18. 郑璟瑜, 殷辰堃, “基于改进小波阈值去噪的MFAC扰动抑制方法”, 自动化应用, Vol.7 , no.4 , pp.34-37, 2016
  19. Ying Ding, Shangtai Jin and Chenkun Yin, “ILC based perimeter control for an urban traffic network”, in Proceedings of the 14th International Conference on Control, Automation, Robotics and Vision (ICARCV 2016), Phuket, Thailand, Nov. 2016
  20. Shida Liu, Zhongsheng Hou and Chenkun Yin, “Data-driven modeling for UGI gasification processes via an enhanced genetic BP neural network with link switches,” IEEE Transactions on Neural Networks and Learning Systems, Vol.27, no.12, pp. 2718-2729, 2016
  21. Zhongsheng Hou, Shida Liu and Chenkun Yin, “Local learning-based model-free adaptive predictive control for adjustment of oxygen concentration in syngas manufacturing industry,” IET Control Theory & Applications, special issue on “Data-driven Control, and Data-Based System Modelling, Monitoring, and Control”, Vol.10, no.12, pp. 1384-1394, 2016
  22. Yanlin Wang and Chenkun Yin, “Study on vehicle fuel consumption and emission characteristics based on floating vehicle data of Beijing”, in Advances in Engineering Research (AER) Vol. 107 - 2nd International Conference on Materials Engineering and Information Technology Applications (MEITA 2016), Qingdao, China, Dec. 24-25, 2016, pp.413-419
  23. Shuo Zhen, Zhongsheng Hou and Chenkun Yin, “A novel data-driven predictive control for networked control systems with random packet dropouts”, in Proceedings of 2017 IEEE the 6th Data-Driven Control and Learning Systems Conference, Chongqing, China, May 26-27, 2017, pp. 335-340
  24. Xian Yu, Zhongsheng Hou and Chenkun Yin, “Iterative learning control for discrete-time nonlinear systems based on adaptive tuning of 2D learning gain”, in Proceedings of the 36th Chinese Control Conference, Dalian, China, July 26-28, 2017, pp. 3581-3586
  25. Haijun Gong, Chenkun Yin, Fang Zhang, Zhongsheng Hou and Ruikun Zhang, “A path planning algorithm for unmanned vehicles based on target-oriented rapidly-exploring random tree”, in Proceedings of 2017 11th Asian Control Conference (ASCC), Gold Coast, Australia, Dec. 17-20, 2017, pp. 760-765
  26. 丁莹, 金尚泰, 殷辰堃, 侯忠生, 城市交通区域的迭代学习边界控制, 控制与决策, vol.33, no.4, pp. 633-638, 2018
  27. Zhongsheng Hou, Xian Yu and Chenkun Yin, “A data-driven iterative learning control framework based on controller dynamic linearization”, in Proceedings of American Control Conference, Milwaukee, USA, June 27-29, 2018, pp. 5588 - 5593
  28. Yongqiang Li, Chengzan Yang, Zhongsheng Hou, Yuanjing Feng and Chenkun Yin, “Data-driven approximate Q-learning stabilization with optimality error bound analysis,” Automatica, vol. 103, pp. 435-442, 2019
  29. 殷辰堃, 侯忠生, “面向工科研究生的“最优化理论、方法及应用”课程教学改革浅析”, 聚焦“双一流”建设 推动研究生教育高质量发展—北京交通大学研究生教育研究与改革论文集（2018）, pp.420-424, 2019
  30. Xuhuan Hao, Chenkun Yin, Zhongsheng Hou and Shangtai Jin, “Ramp metering via feedback-aided iterative learning control for freeway traffic systems under iteration-varying boundary conditions”, in Proceedings of Chinese Automation Congress, Hangzhou, China, November 22-24, 2019, pp. 122-127 
  31. Shuangshuang Xiong, Zhongsheng Hou and Chenkun Yin, “Quasi-Newton method based control design for unknown nonlinear systems with inputs constraints”, SCIENCE CHINA Information Sciences, vol.63, no.5, 2020
  32. Ke Pang, Yanxin Zhang and Chenkun Yin, “A Decision-making method for self-driving based on deep reinforcement learning”, Journal of Physics: Conference Series, vol.1576, 012025, 2020
  33. Ruijie Zhao, Yanxin Zhang, Zhiqing Huang and Chenkun Yin. “End-to-end spatiotemporal attention model for autonomous driving”, in Proceedings of 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), Chongqing, China, June 12-14, 2020, pp. 2649-2653
  34. Haoran Zhang, Chenkun Yin and Yanxin Zhang, “Motion planning using reinforcement learning method for underactuated ship berthing”, in Proceedings of the 16th IEEE International Conference on Control & Automation (ICCA), Sapporo, Hokkaido, Japan, Oct. 9-11, 2020 (virtual), pp. 384-359
  35. Honghai Ji, Lingling Fan, Xindong Gui, Chenkun Yin and Rongmin Cao, “Data-driven adaptive filtering for fault diagnosis of a class of nonlinear discrete-time systems”, in Proceedings of 2020 IEEE the 9th Data-Driven Control and Learning Systems Conference, Liuzhou, China, Nov. 20-22, 2020, pp. 697-701
  36. Zhenxuan Li, Zhongsheng Hou and Chenkun Yin, “Spatial adaptive iterative learning Control for automatic driving of high speed train”, in Proceedings of 2020 IEEE the 9th Data-Driven Control and Learning Systems Conference, Liuzhou, China, Nov. 20-22, 2020, pp. 1440-1445
  37. Hansong Yu, Junwei Kong, Ye Ren and Chenkun Yin, “On the urban link fundamental diagram based on velocity-weighted flow and queue length”, Symmetry, vol.12, no.11, 1852, 2020
  38. Haoran Zhang, Chenkun Yin and Yanxin Zhang, “Self-guided actor-critic: reinforcement learning from adaptive expert demonstrations”, in Proceedings of 2020 59th IEEE Conference on Decision and Control (CDC 2020), Jeju Island, Korea, Dec.14-18, 2020 (virtual), pp. 572-577
  39. Ruochuan Yu, Tao Tang, Chenkun Yin, Jing Xun, Jiayi Xi, and Xiaobin Zheng, “Iterative learning based train stop control with initial state shifts for urban rail transit”, in Proceedings of 2021 IEEE 10th Data-Driven Control and Learning Systems Conference, Suzhou, China, May 14-16, 2021, pp. 478-483
  40. Huiying Wu, Shangtai Jin, Chenkun Yin, Jianmin Zheng and Zhongsheng Hou, “Model free adaptive predictive tracking control for robot manipulators with uncertain parameters”, in Proceedings of 2021 IEEE 10th Data-Driven Control and Learning Systems Conference, Suzhou, China, May 14-16, 2021, pp. 1571-1576
  41. Zihao Wang, Yanxin Zhang, Chenkun Yin and Zhiqing Huang, “Multi-agent Deep Reinforcement Learning based on Maximum Entropy”, in IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC 2021), Chongqing, China, June 18, 2021, pp. 1402-1406
  42. Ru Fang, Chenkun Yin, Shangtai Jin and Kaiting Zhang, “Switched perimeter control for two-region urban traffic networks with dynamic macroscopic fundamental diagrams”, in Proceedings of Chinese Automation Congress (CAC2021), Beijing, China, October 22-24, 2021, pp.7452-7457
  43. 殷辰堃, 方茹, 李拓, “基于交通流时间序列相似性的NCut城市路网分区”, 交通运输工程学报, vol.21, no.5, pp. 238-250, 2021
  44. Zhenxuan Li, Chenkun Yin, Honghai Ji and Zhongsheng Hou, “Constrained spatial adaptive iterative learning control for trajectory tracking of high speed train”, IEEE Transactions on Intelligent Transportation Systems, vol.23, no.8, pp. 11720-11728, 2022
  45. Zhenxuan Li, Zhongsheng Hou, Ruikun Zhang and Chenkun Yin, “Robust point-to-point iterative learning control for high speed trains with model uncertainty and wind gust”, Asian Journal of Control, 2022 (online)
  46. Hongxuan Ji, and Chenkun Yin, “Application of soft actor-critic reinforcement learning to a search and rescue task for humanoid robots,” in Proceedings of 2022 China Automation Congress (CAC), Xiamen, China, November 25-27, 2022, pp.3954-3960
  47. Panpan Zhu, Shangtai Jin, Xuhui Bu, Zhongsheng Hou, and Chenkun Yin, "Model-free adaptive control for a class of MIMO nonlinear cyber-physical systems under false data injection attacks,” IEEE Transactions on Control of Network Systems, vol.10, no.1, pp.467-478, 2023
  48. 殷辰堃, 纪宏萱, 张严心, “复杂可交互场景下基于异策略分层强化学习的搜救机器人自主决策”, 北京工业大学学报, 2023
  49. 张严心, 孔涵, 王子豪, 殷辰堃, “基于MASAC的分布式优先经验回放机制”, 北京工业大学学报, 2023
  50. Chengxi Zhang, Jing Xun, Zhihui Ji, Chenkun Yin and Jiang Cao, “Outlier Detection of Traction Energy Consumption Based on Local Density and Cluster for Time Series Data,” in Proceedings of 2023 IEEE 12th Data-Driven Control and Learning Systems Conference, Xiangtan, China, May 12-14, 2023, pp. 1288-1295
  51. Zhiyang Zhang, Zhenxuan Li, Shuang Guo and Chenkun Yin, “A novel successive updating scheme of iterative learning control for networked control system with output data dropouts,” in Proceedings of 2023 IEEE 12th Data-Driven Control and Learning Systems Conference, Xiangtan, China, May 12-14, 2023, pp. 1702-1707
  52. 王子豪, 张严心,黄志清, 殷辰堃, “部分可观测下基于RGMAAC算法的多智能体协同,” 控制与决策, vol 38, no.5, pp.1267-1277, 2023

专著/译著

专利

  1. 侯忠生, 李振轩, 任天琦, 殷辰堃, 一种列车的隧道附加空气阻力迭代学习辨识方法, 发明专利, 专利号: ZL 201510685059.3, 2018

软件著作权

获奖与荣誉


  • 网络化系统的数据驱动学习控制，河南省自然科学奖二等奖（排名4/4），2022
  • 非线性不确定系统的迭代学习控制理论与方法，CAA自然科学奖二等奖（排名3/4），中国自动化学会，2022
  • 基于高阶内模的迭代学习控制及应用，北京交通大学优秀博士论文，北京交通大学，2011
  • 北京交通大学电子信息工程学院优秀班主任，2017年


社会兼职

  • 中国自动化学会数据驱动控制、学习与优化专业委员会副秘书长、通讯员；
  • IEEE Transactions on Systems, Man, and Cybernetics、IEEE Transactions on Industrial Electronics、IEEE Transactions on Neural Networks and Learning Systems、Asian Journal of Control、Neurocomputing、自动化学报、控制与决策等学术期刊和若干控制领域会议的审稿人；
  • 《北京工业大学学报》青年编委。
  • IEEE Data Driven Control and Learning Systems Conference（DDCLS）会议秘书、AE。