Tracking control of drilling robot feed force based on an equivalent-input-disturbance
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摘要:
煤矿井下施工瓦斯抽采孔作业过程中，钻孔机器人给进系统用于钻进过程加压、减压和给进。针对复杂地层不确定性扰动影响钻孔机器人工作性能和钻孔施工质量及效率的问题，首先分析钻孔机器人的结构组成和钻进施工工艺，根据其给进系统的工作原理，建立了减压阀控制数学模型，获得了控制输入量电磁铁电流与控制输出量减压阀出口压力的映射关系，并在明确给进力驱动方式的基础上对整个给进系统进行控制建模。随后设计了钻孔机器人给进力跟踪控制系统，使用Luenburger全维状态观测器重构被控对象状态，建立基于等价输入干扰估计(EID)与补偿的控制结构，设计了状态反馈控制器、状态观测器和干扰估计器增益矩阵，实现给进力闭环控制系统稳定的同时具有满意的跟踪与扰动抑制性能。最后利用Matlab软件搭建数值仿真模型，以某煤矿井下实际钻进施工时给进系统的实测钻进数据信号为例进行仿真研究，以给进力为控制目标，实测减压阀输出压力波动为依据设计外部扰动信号，分别采用所提EID控制方法和PID控制方法进行了对比仿真。结果表明：所提方法获得了比PID方法更小的稳态跟踪误差峰峰值，且跟踪误差更小，保证了给进系统稳定运行，具有较好的跟踪与扰动抑制性能。研究结果对提高钻孔机器人适应复杂煤层负载变化，保证其工作性能和安全高效施工提供了控制理论基础。
Abstract:During the underground construction of gas extraction hole in coal mine, the feeding system of drilling robot is used for pressurization, decompression and feeding in drilling process. In view of the problem that the uncertain disturbance of complex strata affects the working performance of drilling robot and the quality and efficiency of drilling construction, the structural composition and drilling construction technology of drilling robot were analyzed at first. The mathematical model of pressure reducing valve control was established according to the working principle of its feed system, and the mapping relationship between the control input, the electromagnet current, and the control output, the outlet pressure of pressure reducing valve, was obtained. Then, control modeling was conducted for the whole feed system on the basis of defining the driving mode of feed force. Secondly, the feed force tracking control system of the drilling robot was designed. Meanwhile, the Luenburger full-state observer was used to reconstruct the state of the controlled object, and the control structure based on equivalent-input-disturbance (EID) estimation and compensation was established. Besides, the gain matrix was designed for the state feedback controller, state observer and disturbance estimator, to realize the stability of the feed force closed-loop control system with satisfactory tracking and disturbance suppression performance. Finally, the numerical simulation model was built using the Matlab software. Specifically, the simulation research was carried out with the measured drilling data signal of the feed system in the actual drilling construction of a coal mine. In addition, the external disturbance signal was designed with the feed force as the control target and the measured pressure fluctuation of the pressure reducing valve as the basis. Further, comparative simulation was conducted with the proposed EID control method and PID control method respectively. The results show that the proposed method has a smaller peak-to-peak value of the steady-state tracking error than the PID method, as well as a smaller tracking error, which ensures the stable operation of the feed system and has better tracking and disturbance suppression performance. Generally, the research results of this paper provide a control theoretical basis for improving the adaptability of drilling robots to complex coal seam load changes, and ensuring their working performance and safe and efficient construction.
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图 3 减压阀电流控制传递函数方框图
Fig. 3 Transfer function for current control of pressure reducing valve
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图 5 减压阀阀门出口压力现场数据拟合曲线
Fig. 5 Field data fitting curve for outlet pressure of pressure reducing valve
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图 6 钻孔机器人给进系统给进力跟踪控制结果
Fig. 6 Force tracking control results of drilling robot feed system
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图 7 钻孔机器人给进系统跟踪误差与扰动抑制误差
Fig. 7 Tracking error and disturbance suppression error of drilling robot feed system
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图 8 与PID控制方法的给进系统给进力跟踪控制对比结果
Fig. 8 Comparison results of Force tracking control of feed system with PID control method
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图 9 与PID控制方法的给进系统跟踪误差对比结果
Fig. 9 Comparison results of tracking error of the feed system with PID control method
表 1 减压阀模型仿真参数
Table 1 Simulation parameter of pressure reducing valve model
参数 数值 参数 数值 阀芯质量
$m/{\rm{kg}}$0. 5 阀芯流量
系数${C_{\rm{d}}}$0.62 油液密度
$\rho /({\rm{kg}} \cdot {{\rm{m}}^{ - 3} })$900 阀芯通径
$D$/m$6 \times {10^{ - 3}}$ 阀芯黏性摩擦
系数$b/({\rm{N\cdot s} } \cdot { {\rm{m} }^{ - 1} })$0.5 弹簧刚度
$k/({\rm{N} } \cdot {\rm{m} }^{-1})$2500 油液体积弹性模量
$E/({\rm{N}} \cdot {{\rm{m}}^{ - 2} })$$1.4 \times {10^9}$ 减压阀出口受控
腔初始容积$V/{{\rm{cm}}^3}$20 
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表 2 EID与PID控制方法的误差数据对比
Table 2 Comparison of error data of EID and PID control methods
kN 方法 EIS EITA ERMS PID 176430 41243 104.9420 EID 0.450 6 19.142 5 0.167 7 注：EIS、EITA、ERMS分别为平方误差、绝对误差、均方根误差。
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