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WANG Yunfei,ZHAO Jiyun,ZHANG He,et al. Straightness control method of hydraulic support group pushing system based on neural network compensation[J]. Coal Science and Technology,2024,52(11):174−185. DOI: 10.12438/cst.2024-0951
Citation: WANG Yunfei,ZHAO Jiyun,ZHANG He,et al. Straightness control method of hydraulic support group pushing system based on neural network compensation[J]. Coal Science and Technology,2024,52(11):174−185. DOI: 10.12438/cst.2024-0951

Straightness control method of hydraulic support group pushing system based on neural network compensation

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  • Received Date: July 05, 2024
  • Available Online: November 03, 2024
  • Straightness control of fully mechanized mining face is one of the key technologies to realize intelligent mining, and the position control performance of the hydraulic support push cylinder directly affects the straightness level of the mining face, but the parameter uncertainty, the modeling error and the unknown external disturbances of the push cylinder electro-hydraulic system have increased the difficulty of the position control of the hydraulic support push system. Firstly, the mathematical model of the electro-hydraulic system of the hydraulic support push cylinder is established, which is transformed into Brunovsky standard form taking into account the actual working condition that the push cylinder has only measurable position information. Secondly, a high-order sliding mode state observer is designed to estimate other system states using the measurable position information, while a radial-based neural network-based disturbance observer is designed to estimate and compensate the unknown disturbance forces of the system in real time with using the estimated system state information as the learning data. Thirdly, an output feedback robust controller is proposed for the hydraulic support push cylinder with Backstepping design principle, and the stability of the whole closed-loop control system is verified by Lyapunov theory. Fourthly, a simulation model is established based on the actual physical parameters of the ZY3200/08/18D hydraulic support push cylinder, and the simulation results show that the final position accuracy of the designed controller is improved by 77.19% compared with traditional PI controller, and the estimation accuracy of the neural network compensator for the loads of different cylinders are 64.41% and 75.38%, respectively. Finally, to further verify the effectiveness of the proposed controller, a hydraulic support group multi-cylinder control system test rig is built and the pulling process experiments are carried out. The experimental results showed that the average tracking accuracy of the new controller is improved by 47.23%, the final position accuracy is improved by 75.00% and the average synchronization error of adjacent cylinders is improved by 47.08% compared with the PI controller. The research results provide an idea for the dynamic analysis and straightness control of hydraulic support pushing system.

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