Volume 50 Issue 8
Aug.  2024
Turn off MathJax
Article Contents
Article Navigation >  Journal of Mine Automation  > 2024  >  50(8): 135-143
MAO Qinghua, CHEN Yanzhang, MA Cheng, et al. Research on pitch control of coal mine roadheader based on fuzzy neural network PID[J]. Journal of Mine Automation，2024，50（8）：135-143.  doi: 10.13272/j.issn.1671-251x.2024070014
Citation: MAO Qinghua, CHEN Yanzhang, MA Cheng, et al. Research on pitch control of coal mine roadheader based on fuzzy neural network PID[J]. Journal of Mine Automation，2024，50（8）：135-143.  doi: 10.13272/j.issn.1671-251x.2024070014
shu

Research on pitch control of coal mine roadheader based on fuzzy neural network PID

doi: 10.13272/j.issn.1671-251x.2024070014
  • 1.

    College of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China

  • 2.

    Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Detection and Control, Xi'an 710054, China

  • 3.

    Shaanxi Shanmei Huangling Mining Co., Ltd., Yan'an 727307, China

  • Received Date: 2024-07-08
  • Rev Recd Date: 2024-08-19
    • Available Online: 2024-08-12
    Abstract
  • Currently, PID control method is mainly used for the pitch control of coal mine roadheader, and the control precision is not high in the case of time-varying and nonlinear hydraulic system during the pitch control of roadheader. The pitch control of roadbeader is realized by controlling the stroke of the hydraulic cylinder. Combining the traditional PID algorithm with fuzzy control and neural network, the accuracy of the stroke control of the hydraulic cylinder can be effectively improved. In order to solve the above problems, a pitch control method for coal mine roadheader based on fuzzy neural network PID is proposed. By analyzing the kinematic relationship of the support part of the roadheader, the mathematical relationship between the pitch angle and the hydraulic cylinder of the support part is obtained. The working principle of the pitch control hydraulic system of the roadheader is introduced, and the hydraulic system and its transfer function model are established. The method combines fuzzy control with neural networks to form a fuzzy neural network. The method optimizes PID control parameters by using the fuzzy neural network. The method combines the mathematical model of the support mechanism and the transfer function model of the hydraulic system to establish a fuzzy neural network PID control model for the pitch angle of the roadheader. It achieves automatic and precise control of the pitch mechanism of the coal mine roadheader. This method can make the pitch mechanism of the roadheader reach the preset position more quickly and accurately, solving the time-varying and nonlinear problems in the pitch control of roadheader. The simulation results show that the fuzzy neural network PID control algorithm reduces tracking errors by 69.34% and 74.49% respectively compared to fuzzy PID and PID control algorithms. The method simulates the pitch control of coal mine roadheaders under sudden and following working conditions through hydraulic cylinder displacement control. The results show that compared with fuzzy PID and PID control algorithms, the fuzzy neural network PID control algorithm has the smallest pitch control tracking error, shortens the average response time to position signals by 27.22% and 50.33% respectively, and has better dynamic control performance.

     

    • FullText(HTML)
  • loading
    • References(21)
  • [1]
    葛世荣,郝尚清,张世洪,等. 我国智能化采煤技术现状及待突破关键技术[J]. 煤炭科学技术,2020,48(7):28-46.

    GE Shirong,HAO Shangqing,ZHANG Shihong,et al. Status of intelligent coal mining technology and potential key technologies in China[J]. Coal Science and Technology,2020,48(7):28-46.
    [2]
    臧富雨,王凯硕,吉晓冬,等. 悬臂式掘进机俯仰角调控系统仿真研究[J]. 工矿自动化,2019,45(5):62-67.

    ZANG Fuyu,WANG Kaishuo,JI Xiaodong,et al. Simulation research on pitch angle control system of boom roadheader[J]. Industry and Mine Automation,2019,45(5):62-67.
    [3]
    张晓光,杨悦,孙彦景,等. 基于多频连续波相位差测距的掘进机位姿识别方法[J]. 煤炭学报,2020,45(6):2056-2064.

    ZHANG Xiaoguang,YANG Yue,SUN Yanjing,et al. Pose recognition method of roadheader based on multifrequency continuous-wave phase-difference ranging[J]. Journal of China Coal Society,2020,45(6):2056-2064.
    [4]
    ZHANG Minjun,LYU Fuyan,FU Shichen,et al. Study on the pitch angle control of a robotized hydraulic drive roadheader using different control methods[J]. Journal of Mechanical Science and Technology,2018,32(10):4893-4901. doi: 10.1007/s12206-018-0937-7
    [5]
    张敏骏,吉晓冬,李旭,等. 掘进机姿态调整模型辨识方法与精准控制[J]. 西安交通大学学报,2021,55(6):9-17.

    ZHANG Minjun,JI Xiaodong,LI Xu,et al. Method of model identification and precise control for tunnel boring machine body posture adjustment[J]. Journal of Xi'an Jiaotong University,2021,55(6):9-17.
    [6]
    王东杰,王鹏江,李悦,等. 掘进机截割臂自适应截割控制策略研究[J]. 中国机械工程,2022,33(20):2492-2501.

    WANG Dongjie,WANG Pengjiang,LI Yue,et al. Research on adaptive cutting control strategy of roadheader cutting arms[J]. China Mechanical Engineering,2022,33(20):2492-2501.
    [7]
    张旭辉,石硕,杨红强,等. 悬臂式掘进机自主调速截割控制系统[J]. 工矿自动化,2023,49(1):80-89.

    ZHANG Xuhui,SHI Shuo,YANG Hongqiang,et al. Boom-type roadheader autonomous speed regulation cutting control system[J]. Journal of Mine Automation,2023,49(1):80-89.
    [8]
    刘志森. 悬臂式掘进机截割部恒功率调速控制系统研究[D]. 阜新:辽宁工程技术大学,2012.

    LIU Zhisen. Research on constant power speed regulation control system for cutting part of cantilever roadheader[D]. Fuxin:Liaoning Technical University,2012.
    [9]
    王苏彧,田劼,吴淼. 纵轴式掘进机截割轨迹规划及边界控制方法研究[J]. 煤炭科学技术,2016,44(4):89-94,118.

    WANG Suyu,TIAN Jie,WU Miao. Study on cutting trace planning of longitudinal roadheader and boundary control method[J]. Coal Science and Technology,2016,44(4):89-94,118.
    [10]
    王鹏江,沈阳,宗凯,等. 结合LSTM深度学习和模糊推理控制的巷道掘进机智能联合截割策略与方法 [J/OL]. 煤炭学报:1-14[2024-06-21]. https://doi.org/ 10.13225/j.cnki.jccs.2023.1612.

    WANG Pengjiang,SHEN Yang,ZONG Kai,et al. Intelligent joint cutting strategy and method of roadheader combined with LSTM deep learning and fuzzy reasoning control[J/OL]. Journal of China Coal Society:1-14[2024-06-21]. https://doi.org/10.13225/ j.cnki.jccs.2023.1612.
    [11]
    CHELUSZKA P,SOBOTA P,GŁUSZEK G. Studies of behaviour of the automatic control system of roadheader cutting heads movement[J]. MATEC Web of Conferences,2019,252. DOI: 10.1051/matecconf/201925209002.
    [12]
    郭伦锋,郭一楠,蒋康庆,等. 掘进机姿态参数测量及解算方法[J]. 工矿自动化,2021,47(12):46-54.

    GUO Lunfeng,GUO Yinan,JIANG Kangqing,et al. Measurement and calculation method of attitude parameters of roadheader[J]. Industry and Mine Automation,2021,47(12):46-54.
    [13]
    费烨,孙波,林闯. EBZ160悬臂式掘进机液压系统设计[J]. 液压与气动,2015,39(2):103-106. doi: 10.11832/j.issn.1000-4858.2015.02.026

    FEI Ye,SUN Bo,LIN Chuang. The design for hydraulic system of EBZ160 cantilever tunneling machine[J]. Chinese Hydraulics & Pneumatics,2015,39(2):103-106. doi: 10.11832/j.issn.1000-4858.2015.02.026
    [14]
    王志武. 掘进机行走机构液压系统液压冲击的分析与处理[J]. 机床与液压,2013,41(4):108-109. doi: 10.3969/j.issn.1001-3881.2013.04.032

    WANG Zhiwu. Analysis and treatment of hydraulic shock in hydraulic system of roadheader traveling mechanism[J]. Machine Tool & Hydraulics,2013,41(4):108-109. doi: 10.3969/j.issn.1001-3881.2013.04.032
    [15]
    陶建峰,刘成良. 全断面岩石隧道掘进机液压技术研究现状[J]. 液压与气动,2015,39(6):1-5,12. doi: 10.11832/j.issn.1000-4858.2015.06.001

    TAO Jianfeng,LIU Chengliang. Review of technical research for hydraulic system of tunnel boring machine[J]. Chinese Hydraulics & Pneumatics,2015,39(6):1-5,12. doi: 10.11832/j.issn.1000-4858.2015.06.001
    [16]
    张敏骏. 悬臂式掘进机自主纠偏与位姿控制研究[D]. 北京:中国矿业大学(北京),2019.

    ZHANG Minjun. Research on autonomous correction and pose control of cantilever tunneling machine[D]. Beijing:China University of Mining & Technology-Beijing,2019.
    [17]
    张建广. 悬臂式掘进机自适应截割控制系统研究[J]. 煤炭科学技术,2016,44(2):148-152.

    ZHANG Jianguang. Study on adaptive cutting control system of boom-type roadheader[J]. Coal Science and Technology,2016,44(2):148-152.
    [18]
    雷孟宇,张旭辉,杨文娟,等. 煤矿掘进装备视觉位姿检测与控制研究现状与趋势[J]. 煤炭学报,2021,46(增刊2):1135-1148.

    LEI Mengyu,ZHANG Xuhui,YANG Wenjuan,et al. Research status and trend of visual pose detection and control of coal mine tunneling equipment[J]. Journal of China Coal Society,2021,46(S2):1135-1148.
    [19]
    范子彦,李立君,李宇航,等. 油茶果采摘机阀控液压马达模糊神经网络PID控制[J]. 液压与气动,2021,45(11):76-85. doi: 10.11832/j.issn.1000-4858.2021.11.011

    FAN Ziyan,LI Lijun,LI Yuhang,et al. Fuzzy neural network PID control of valve-controlled hydraulic motor for camellia fruit picking machine[J]. Chinese Hydraulics & Pneumatics,2021,45(11):76-85. doi: 10.11832/j.issn.1000-4858.2021.11.011
    [20]
    敖邦乾,姜孝均,董泽芳,等. 基于神经网络−PID控制的水面无人艇控制系统设计[J]. 控制工程,2024,31(7):1178-1184.

    AO Bangqian,JIANG Xiaojun,DONG Zefang,et al. Design of unmanned surface vehicle control system based on neural network-PID control[J]. Control Engineering of China,2024,31(7):1178-1184.
    [21]
    DHIMISH M,HOLMES V,MEHRDADI B,et al. Comparing Mamdani Sugeno fuzzy logic and RBF ANN network for PV fault detection[J]. Renewable Energy,2018,117:257-274. doi: 10.1016/j.renene.2017.10.066
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(12)  / Tables(5)

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (102) PDF downloads(12) Cited by()
    Proportional views
    Related

    苏ICP备 05016349号-2

    Supported by: Beijing Renhe Information Technology Co. Ltd.  Visits：    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return