采用扩张状态观测器双闭环复合策略的液压支架新型阀控缸系统平滑精准控制方法

廖瑶瑶; 魏光耀; 张嘉哲; 廉自生

doi:10.7652/xjtuxb202611012

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采用扩张状态观测器双闭环复合策略的液压支架新型阀控缸系统平滑精准控制方法

更新时间：2026-11-09

- 采用扩张状态观测器双闭环复合策略的液压支架新型阀控缸系统平滑精准控制方法
- Smooth and Precise Control Method for a Novel Valve-Controlled Cylinder System in Hydraulic Supports Based on a Dual Closed-Loop Compound Strategy with Extended State Observer
- 西安交通大学学报 2026年60卷第11期页码：133-144
- 作者机构：
  
  太原理工大学机械工程学院，030024，太原
  太原理工大学智能采矿装备技术全国重点实验室，030024，太原
- 作者简介：
  
  廖瑶瑶（1986—），男，教授，博士生导师。
- 基金信息：
  
  国家自然科学基金资助项目(52575069);山西省自然科学基金资助项目(202303021211064);中国博士后科学基金资助项目(2021M702419)
- DOI：10.7652/xjtuxb202611012
  中图分类号： TH137
- 收稿：2026-04-28，
  
  网络首发：2026-07-31，
  
  纸质出版：2026-11-10
- 稿件说明：
移动端阅览
廖瑶瑶, 魏光耀, 张嘉哲, 等. 采用扩张状态观测器双闭环复合策略的液压支架新型阀控缸系统平滑精准控制方法[J/OL]. 西安交通大学学报,2026,60 (11):133-144. https://doi.org/10.7652/xjtuxb202611012.

LIAO Yaoyao, WEI Guangyao, ZHANG Jiazhe, et al. Smooth and Precise Control Method for a Novel Valve-Controlled Cylinder System in Hydraulic Supports Based on a Dual Closed-Loop Compound Strategy with Extended State Observer[J/OL]. Journal of Xi'an Jiaotong University,2026,60 (11):133-144. https://doi.org/10.7652/xjtuxb202611012.
廖瑶瑶, 魏光耀, 张嘉哲, 等. 采用扩张状态观测器双闭环复合策略的液压支架新型阀控缸系统平滑精准控制方法[J/OL]. 西安交通大学学报,2026,60 (11):133-144. https://doi.org/10.7652/xjtuxb202611012. DOI：

LIAO Yaoyao, WEI Guangyao, ZHANG Jiazhe, et al. Smooth and Precise Control Method for a Novel Valve-Controlled Cylinder System in Hydraulic Supports Based on a Dual Closed-Loop Compound Strategy with Extended State Observer[J/OL]. Journal of Xi'an Jiaotong University,2026,60 (11):133-144. https://doi.org/10.7652/xjtuxb202611012. DOI：

摘要

针对煤矿井下液压支架因采用高压、大流量、高水基开关阀控缸系统而普遍存在的位姿控制精度低、支护群组直线度差及启停液压冲击大等问题，发明了一款三芯随动式矿用高压大流量水基比例阀，提出了基于线性扩张状态观测器（LESO）的双闭环速度-位置复合控制方法，进而采用改进灰狼算法（IGWO）对PID参数进行离线优化。通过搭建仿真模型与试验平台，分别对传统开关控制、PID控制和所提复合控制进行对比测试，结果表明：开关控制和PID控制方式下的最大位置跟踪误差分别为7.50、4.51 mm，而新型速度位置复合控制下的误差仅为1.22 mm，相比前两种传统控制方式，误差降幅分别达83.73%和72.95%；在前两种传统控制方式下，液压缸启停阶段压力超调量分别为102.1%和48.0%，而速度位置复合控制方式下，液压缸压力无超调产生。该研究提出的新型水基比例阀及改进灰狼算法优化参数的扩张状态观测器速度-位置双闭环复合控制策略，成功实现了液压支架推移缸速度与位置的连续平滑调节，消除了系统液压冲击，提升了控制精度，为煤矿智能开采中液压支架高精度姿态控制、支护群组直线度自动校正提供了有效参考。

Abstract

To address the common issues of hydraulic supports in underground coal mines caused by conventional high-pressure

large-flow

and high-water-based on-off valve control systems (such as low posture control accuracy

poor straightness of the support group

and severe hydraulic shock during start and stop operations)

a novel three-spool follow-up proportional valve for high-pressure and large-flow water-based mining applications is developed.A dual closed-loop velocity-position compound control method based on a linear extended state observer (LESO) is proposed

and an improved grey wolf optimizer (IGWO) is employed for the offline optimization of PID parameters.Through the establishment of a simulation model and an experimental platform

comparative tests were conducted among the traditional on-off control

PID control

and the proposed compound control.The results show that the maximum position tracking errors under the on-off control and PID control are 7.50 mm and 4.51 mm

respectively

whereas the error under the novel velocity-position compound control is only 1.22 mm.Compared with the two traditional control methods

the error is reduced by 83.7% and 72.9%

respectively.Under the two traditional control methods

the pressure overshoots during the start and stop phases of the hydraulic cylinder are 102.1% and 48%

respectively

whereas the proposed compound control method completely eliminates pressure overshoot.The novel waterbased proportional valve and the IGWO-optimized velocity-position dual closed-loop compound control strategy proposed in this study successfully achieve continuous and smooth regulation of the velocity and position of the advancing cylinder in the hydraulic support

eliminate hydraulic shock in the system

and improve control accuracy.This provides an effective reference for highprecision posture control of hydraulic supports and automatic straightness correction of the support group in intelligent coal mining.

关键词

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