Event-State-Driven Virtual-Real Interactive Predictive Control Method for Intelligent Tunneling Equipment

WANG Yan; HAN Xiao; WEI Shirui; LENG Jiewu; ZHANG Jiaqi; ZHANG Xuhui; ZHAO Yihui; ZHAO Youjun; CAO Xiangang; HE Longlong

doi:10.7652/xjtuxb202610008

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Event-State-Driven Virtual-Real Interactive Predictive Control Method for Intelligent Tunneling Equipment

Special Topic Intelligent Perception and Autonomous Decision-Making | 更新时间：2026-09-29

- Event-State-Driven Virtual-Real Interactive Predictive Control Method for Intelligent Tunneling Equipment
- Journal of Xi'an Jiaotong University Vol. 60, Issue 10, Pages: 91-102(2026)
- 作者机构：
  
  西安科技大学机械工程学院，710054，西安
  陕西省矿山机电装备智能检测与控制重点实验室，710054，西安
  西安煤矿机械有限公司，710032，西安
  广东工业大学机电工程学院，510006，广州
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202610008
  CLC： TD421.5
- Received：27 January 2026，
  
  Online First：09 April 2026，
  
  Published：10 October 2026
- 稿件说明：
移动端阅览
WANG Yan, HAN Xiao, WEI Shirui, et al. Event-State-Driven Virtual-Real Interactive Predictive Control Method for Intelligent Tunneling Equipment[J/OL]. Journal of Xi'an Jiaotong University,2026,60 (10):91-102. https://doi.org/10.7652/xjtuxb202610008.
DOI：

WANG Yan, HAN Xiao, WEI Shirui, et al. Event-State-Driven Virtual-Real Interactive Predictive Control Method for Intelligent Tunneling Equipment[J/OL]. Journal of Xi'an Jiaotong University,2026,60 (10):91-102. https://doi.org/10.7652/xjtuxb202610008. DOI：

摘要

针对传统掘进机控制方法巷道截割成形效率低、人工依赖性高的问题，提出了一种事件状态驱动的智能掘进设备虚实交互预测控制方法。首先，构建掘进机事件状态模型，将截割轨迹离散为关键状态节点，实时监测截割状态以识别硬岩引发的机身异常偏移，设计事件驱动的虚实状态演变逻辑，实现物理实体与数字孪生体的状态跃迁与同步。其次，构建掘进机数字孪生模型实现截割过程的虚拟映射，基于模型预测控制（MPC）对实际轨迹进行预测，为虚实状态对齐与异常轨迹修正提供虚拟决策，通过数字孪生体与物理实体的虚实交互，实现从状态感知到决策执行的闭环。最后，搭建掘进机虚实交互实验平台开展实验验证，利用算法识别机身异常偏移，根据MPC耦合控制决策实现轨迹修正。结果表明：MPC耦合控制下，轨迹跟踪最大误差由解耦控制的18.5mm降至7.2mm，最大偏差降幅达61.1%。该研究方法可为煤矿巷道掘进装备智能控制提供技术支撑。

Abstract

To address the issues of low roadway cutting and profiling efficiency and high reliance on manual operation in traditional roadheader control methods

an event-state-driven virtual-real interactive predictive control method for intelligent tunneling equipment is proposed. First

an event-state model of the roadheader is constructed to discretize the cutting trajectory into key state nodes. The cutting state is monitored in real time to identify abnormal body offsets caused by hard rock. An event-driven virtual-real state evolution logic is designed to achieve state transition and synchronization between the physical entity and its digital twin. Second

a digital twin model of the roadheader is constructed to achieve virtual mapping of the cutting process. Based on model predictive control (MPC)

the actual trajectory is predicted to provide virtual decision-making for virtual-real state alignment and abnormal trajectory correction. Through virtual-real interaction between the digital twin and the physical entity

a closed loop from state perception to decision execution is realized. Finally

a virtual-real interaction experimental platform for the roadheader is built for experimental verification. Algorithms are utilized to identify abnormal body offsets

and trajectory correction is achieved based on MPC coupling control decisions. The results show that the MPC-based coupling control reduces the maximum trajectory tracking error from 18.5mm to 7.2mm

corresponding to a reduction of 61.1% in the maximum deviation. This research method can provide effective technical support for the intelligent control of coal mine roadway tunneling equipment.

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references

王国法, 任怀伟, 富佳兴.煤矿智能化建设高质量发展难题与路径[J].煤炭科学技术, 2025, 53(1): 1-18.

Wang Guofa, Ren Huaiwei, Fu Jiaxing.Challenge and path of high-quality development of coal mine intelligent construction[J].Coal Science and Technology, 2025, 53(1): 1-18.

王国法, 张金虎, 任怀伟, 等.煤炭高效开采数智技术与成套装备研究及应用[J].煤炭学报, 2025, 50(1): 43-64.

Wang Guofa, Zhang Jinhu, Ren Huaiwei, et al. Research and application practice of digital intelligent technology and complete set of equipment for efficient coalmining[J].Journal of China Coal Society, 2025, 50(1): 43-64.

张旭辉, 杨文娟, 薛旭升, 等.煤矿远程智能掘进面临的挑战与研究进展[J].煤炭学报, 2022, 47(1): 579-597.

Zhang Xuhui, Yang Wenjuan, Xue Xusheng, et al. Challenges and developing of the intelligent remote control on roadheaders in coal mine[J].Journal of China Coal Society, 2022, 47(1): 579-597.

Wang Zhuo, Lin Bi, Li Jinbo, et al. Development status and trend of mine intelligent mining technology [J]. Mathematics, 2025, 13(13): 2217.

张旭辉, 万继成, 杨文娟, 等.煤矿巷道智能掘进技术进展、挑战与趋势[J].煤炭科学技术, 2026, 54(1): 388-410.

Zhang Xuhui, Wan Jicheng, Yang Wenjuan, et al. Development, challenges and future trends of intelligent tunneling technology in coal mine roadways[J].Coal Science and Technology, 2026, 54(1): 388-410.

王虹, 王步康, 张小峰, 等.煤矿智能快掘关键技术与工程实践[J].煤炭学报, 2021, 46(7): 2068-2083.

Wang Hong, Wang Bukang, Zhang Xiaofeng, et al. Key technology and engineering practice of intelligent rapid heading in coal mine[J].Journal of China Coal Society, 2021, 46(7): 2068-2083.

张旭辉, 王甜, 张超, 等.数字孪生驱动的悬臂式掘进机虚拟示教记忆截割方法[J].煤炭学报, 2023, 48(11): 4247-4260.

Zhang Xuhui, Wang Tian, Zhang Chao, et al. DT-driven memory cutting control method using VR instruction of boom-type roadheader[J].Journal of China Coal Society, 2023, 48(11): 4247-4260.

安葳鹏, 闫鹏皓, 张文博, 等.基于K-GRU神经网络的采煤机记忆截割及优化[J].河南理工大学学报(自然科学版), 2024, 43(1): 96-104.

An Weipeng, Yan Penghao, Zhang Wenbo, et al. Memory cutting and optimization of shearer based on K-GRU neural network[J].Journal of Henan Polytechnic University (Natural Science), 2024, 43(1): 96-104.

杨健健, 张强, 吴淼, 等.巷道智能化掘进的自主感知及调控技术研究进展[J].煤炭学报, 2020, 45(6): 2045-2055.

Yang Jianjian, Zhang Qiang, Wu Miao, et al. Research progress of autonomous perception and control technology for intelligent heading[J].Journal of China Coal Society, 2020, 45(6): 2045-2055.

毛君, 杨润坤, 谢苗, 等.煤矿智能快速掘进关键技术研究现状及展望[J].煤炭学报, 2024, 49(2): 1214-1229.

Mao Jun, Yang Runkun, Xie Miao, et al. Research status and prospects of key technologies for intelligent rapid excavation in coal mines[J].Journal of China Coal Society, 2024, 49(2): 1214-1229.

陶飞, 张辰源, 张贺, 等.未来装备探索: 数字孪生装备[J].计算机集成制造系统, 2022, 28(1): 1-16.

Tao Fei, Zhang Chenyuan, Zhang He, et al. Future equipment exploration: digital twin equipment[J]. Computer Integrated Manufacturing Systems, 2022, 28(1): 1-16.

Yang Jialin, Li Haotong, Lin Tingyi, et al. Review on application of digital twin technology in mechanical system fault diagnosis [J].Journal of Technology Innovation and Engineering, 2026, 1(7): 7156.

Nobahar P, Xu Chaoshui, Dowd P, et al. Exploring digital twin systems in mining operations: a review [J]. Green and Smart Mining Engineering, 2024, 1(4): 474-492.

吴淼, 沈阳, 吉晓冬, 等.悬臂式掘进机行走轨迹及偏差感知方法[J].煤炭学报, 2021, 46(7): 2046-2056.

Wu Miao, Shen Yang, Ji Xiaodong, et al. Trajectory and deviation perception method of boom-type roadheader[J].Journal of China Coal Society, 2021, 46(7): 2046-2056.

Zhang Chao, Zhang Xuhui, Yang Wenjuan, et al. An improved NSGA-Ⅱ-based method for cutting trajectory planning of boom-type roadheader [J].Applied Sciences, 2025, 15(4): 2126.

Zhang Xi, Yang Ye, Zhang Xin, et al. A multi-level digital twin construction method of assembly line based on hybrid worker digital twin models [J].Advanced Engineering Informatics, 2024, 62(Part A): 102597.

李娟莉, 姜朔, 谢嘉成, 等.基于采煤机截割路径的动态三维地质模型构建方法[J].东北大学学报(自然科学版), 2021, 42(5): 706-712.

Li Juanli, Jiang Shuo, Xie Jiacheng, et al. Construction method of the dynamic 3-D geological model based on shearer cutting path[J].Journal of Northeastern University (Natural Science), 2021, 42(5): 706-712.

郭逸风, 薛旭升, 马宏伟, 等.综采工作面煤层数据驱动的截割轨迹规划方法[J].煤田地质与勘探, 2026, 54(4): 256-264.

Guo Yifeng, Xue Xusheng, Ma Hongwei, et al. A data-driven method for planning cutting trajectories in fully mechanized mining face coal seams[J].Coalfield Geology and Exploration, 2026, 54(4): 256-264.

Zheng Jinkai, Luan T H, Zhang Yao, et al. Data synchronization in vehicular digital twin network: a game theoretic approach [J].IEEE Transactions on Wireless Communications, 2023, 22(11): 7635-7647.

王岩, 寇浩楠, 张旭辉, 等.数字孪生驱动的智能掘进设备虚实交互控制方法[J].中国矿业大学学报, 2025, 54(2): 330-342.

Wang Yan, Kou Haonan, Zhang Xuhui, et al. Virtual-physical interaction control method for intelligent cantilever roadheader driven by digital twin[J].Journal of China University of Mining & Technology, 2025, 54(2): 330-342.

Dou Yuhan, Wang Hujiang, Wu Bing, et al. Research on the virtual-real interaction system and interaction characteristics of a single-leg of quadruped robots based on digital twin [J].Journal of Bionic Engineering, 2024, 21(5): 2215-2231.

Zan Tao, Jia Xiaolong, Guo Xiaoyu, et al. Research on variable-length control chart pattern recognition based on sliding window method and SECNN-BiLSTM [J]. Scientific Reports, 2025, 15(1): 5921.

王岩, 张旭辉, 曹现刚, 等.掘进工作面数字孪生体构建与平行智能控制方法[J].煤炭学报, 2022, 47(增刊1): 384-394.

Wang Yan, Zhang Xuhui, Cao Xiangang, et al. Construction of digital twin and parallel intelligent control method for excavation face[J].Journal of China Coal Society, 2022, 47(S1): 384-394.

Wang Yan, Yang Zhiwei, Kou Haonan, et al. Event driven dynamics model of operating state evolution for cantilever roadheader [J].Applied Sciences, 2025, 15(8): 4376.

Berberich J, Allgöwer F.An overview of systemstheoretic guarantees in data-driven model predictive control [J].Annual Review of Control, Robotics, and Autonomous Systems, 2025, 8: 77-100.

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