Adaptive Control Method for Initial Support Force of Self-Shifting Temporary Support Based on Pressure Feedback

Rui Li, Dongjie Wang (), Weixiong Zheng, Tong Li and Miao Wu
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Rui Li: School of Mechanical, Electrical & Information Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China
Dongjie Wang: School of Mechanical, Electrical & Information Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China
Weixiong Zheng: School of Energy and Power, Tsinghua University, Beijing 100083, China
Tong Li: School of Mechanical, Electrical & Information Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China
Miao Wu: School of Mechanical, Electrical & Information Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China

Mathematics, 2025, vol. 13, issue 18, 1-30

Abstract: To address the challenge of effective roof support in fully mechanized excavation roadways, this paper proposes an adaptive control method for the initial support force of self-shifting temporary supports based on pressure sensors. First, the mechanical characteristics of the roof in fully mechanized excavation faces were analyzed, a static model of the roadway roof thin plate was established, the mechanical criteria for heading support were determined, and the reasonable calculation of the initial support force and working resistance for heading support was completed. Then, the pressure-control system of the hydraulic cylinder was modeled, achieving real-time online adjustment of PID control parameters based on fuzzy neural network control, and an adaptive control system for initial support force based on feedback from pressure sensors inside the hydraulic cylinder was constructed. Finally, comparative experiments of fuzzy neural network PID (FNN-PID) and fuzzy PID control were conducted in both the AMESim 2304 and Matlab/Simulink 2016 co-simulation environment and real physical scenarios. The effectiveness and advancement of the proposed control algorithm were verified.

Keywords: fully mechanized excavation roadway; heading support; initial support force regulation; pressure feedback; fuzzy neural network (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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