[1]郭一楠,程伟,杨欢,等.锚杆钻机转速的头脑风暴最优自抗扰控制[J].郑州大学学报(工学版),2019,40(03):3.[doi:10.13705/j.issn.1671-6833.2019.03.005]
　Guo Yinan,Cheng Wei,Yang Huan,et al.An Optimal Active-disturbance-rejection Controller for the Rotary Speed of An Anchor-hole Drill Based on Brain Storm Optimization Algorithm[J].Journal of Zhengzhou University (Engineering Science),2019,40(03):3.[doi:10.13705/j.issn.1671-6833.2019.03.005]
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锚杆钻机转速的头脑风暴最优自抗扰控制()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
40
期数:
2019年03期
页码:
3
栏目:
出版日期:
2019-04-30

文章信息/Info

Title:
An Optimal Active-disturbance-rejection Controller for the Rotary Speed of An Anchor-hole Drill Based on Brain Storm Optimization Algorithm
作者:
郭一楠; 程伟; 杨欢; 杨帆; 陆希望
1. 中国矿业大学信息与控制工程学院;2. 山西潞安集团和顺李阳煤业有限公司
Author(s):
Guo Yinan 1; Cheng Wei 1; Yang Huan 1; Yang Fan 1; 2; Lu hope 1
1. School of Information and Control Engineering, China University of Mining and Technology; 2. Shanxi Lu’an Group Heshun Liyang Coal Industry Co., Ltd.
关键词:
头脑风暴优化算法; 自抗扰控制; 钻机转速; 围岩性状; 参数整定
Keywords:
Brainstorm optimization algorithm; ADRC; Rig speed; Surrounding rock properties; parameter setting
DOI:
10.13705/j.issn.1671-6833.2019.03.005
文献标志码:
A
摘要:
锚杆钻机作为巷道掘进支护的关键设备，其控制主要依赖于操作人员经验.不合理的钻机转速经常导致别杆、断杆等故障发生，大大降低了钻进效率.考虑到钻机回转系统固有的非线性和参数时变性，以及由多种因素引起的内外扰动，本文提出锚杆钻机转速的最优自抗扰控制方法.该方法基于钻进围岩顶板条件，动态估计转速的给定值；为兼顾系统的动、稳态控制性能要求，采用头脑风暴优化算法，实现自抗扰控制参数优化整定.基于Matlab和AMESim的联合仿真平台，面向单一围岩，考虑无扰和存在外部扰动的两种情况，实验表明相比于最优PID控制方法，所提最优自抗扰控制器具有更好的动、稳态性能和更强的鲁棒性.
Abstract:
As the key equipment of tunneling a roadway, controlling the anchor-hole drills mainly depends on the operator’s experience. Improper rotary speed of an anchor-hole drill generally results in sticking or breaking pipes, which reduces the drilling efficiency. Especially, the nonlinearities and time-varying parameters, as well as the disturbances resulted from various factors in the anchor-hole drill rotary system shall be taken into consideration. A novel optimal active-disturbance-rejection controller is proposed in the paper. The set value of the rotary speed is dynamically estimated in terms of the geological condition of surrounding rocks. Brain storm optimization algorithm is employed to find the optimal parameters of the controller, which have the best dynamic and steady control performances. Based on the simulation platform composed of AMESim and Matlab, the experimental results for a single surrounding rock with or without the external disturbance show that the proposed ADRC controller has better dynamic and steady performances and stronger robustness than the optimal PID controller.

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更新日期/Last Update: 2019-04-16