FAN Jingdao,YAN Zhenguo,LI Chuan,et al. Research and application of cooperative control theory and key technologies for intelligent coal miningJ. Journal of China Coal Society,2026,51(1):793−805. DOI: 10.13225/j.cnki.jccs.2025.0510
Citation: FAN Jingdao,YAN Zhenguo,LI Chuan,et al. Research and application of cooperative control theory and key technologies for intelligent coal miningJ. Journal of China Coal Society,2026,51(1):793−805. DOI: 10.13225/j.cnki.jccs.2025.0510

Research and application of cooperative control theory and key technologies for intelligent coal mining

  • In response to the “intelligence-capability disconnect” paradox in intelligent coal mining manifests as: insufficient operational environment perception, poor adaptability of smart equipment, and limited collaborative capacity, resulting in the dilemma of “intelligence without capability, capability without intelligence”. The collaborative control theory and technological applications in intelligent coal mining were thoroughly investigated, with systematic analyses conducted on the integration challenges between autonomous systems, environmental perception, and multi-agent coordination. Based on the ternary space fusion theory (HPC) and from the perspective of secondary production space, the fundamental definition and characteristics of intelligent mining have been systematically clarified. The principle of intelligent mining collaborative control has been systematically constructed. The characteristics of multi-agent systems have been thoroughly analyzed. A data-driven multi-agent collaborative control strategy encompassing task allocation, path planning, and resource optimization has been explicitly defined. The key technologies of intelligent mining collaborative control, including environment pre-perception, autonomous operation decision-making, and equipment self-organization, have been systematically analyzed, specifically involving GNN-based multi-environmental perception fusion, SOM-driven autonomous operation matching, and large-scale graph computing-enabled equipment self-organization, achieving multidimensional perception fusion, adaptive parameter adjustment, intelligent decision-making, and precise control. The relevant technologies have been implemented in engineering practices at both the intelligent fully-mechanized mining face of Huangling Mining Area and the 5G-based intelligent mining operations of Bala Su Coal Mine under Yanchang Mining Group. These applications have significantly enhanced the intelligence level of coal mining operations, optimized resource allocation, and achieved breakthroughs in the intelligent production model characterized by “remote control, automated extraction, manned inspection, and guard-free operation”. This provides both theoretical guidance and practical references for the collaborative control of intelligent coal mining.
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