Autonomous steering control for tunnel boring machines
Zhe Zheng, Kaidi Luo, X.-L. Tan, Lianhui Jia, Mingrui Xie, Haibo Xie, Lijie Jiang, Guofang Gong, Huayong Yang, Dong Seop Han
Abstract
Driven by the growing requirements for long-distance tunnels, autonomous steering control is a productive research to surpass the limitations of manual operation in steering control of tunnel boring machines (TBMs). However, existing reviews have not yet systematically discussed it from the perspective of hierarchical control. Besides, they mainly focused on how to use artificial intelligence to accomplish this task, while neglecting the knowledge-based studies. Therefore, based on the definition of hierarchical control, this paper surveys a wide range of literature on autonomous steering control from three aspects: 1) Perception layer acquires information about attitude deviation, geological conditions, and shield tail clearance; 2) Decision layer gives appropriate commands for thrust system, making the actual tunnel axis approach the designed one; 3) Execution layer designs feedback-based controllers to ensure the hydraulic cylinders accurately implement those commands. Ultimately, some future directions are highlighted to improve the efficiency and stability of tunneling .