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High-precision position control of belt drive system based on OPC communication

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Abstract

Aiming at the problem of low precision of high-speed start-stop position of belt drive system controlled by PLC, the text takes the belt drive system driven by the brushless DC servo motor (BLDCM) as the research object, studying the PLC intelligent control system based on OPC communication. Firstly, a mathematical model is established. Then, a fuzzy adaptive PID control algorithm is proposed to perform self-tune the tape speed and its deviation rate. Finally, the simulation comparison is made with the traditional PID control in terms of speed and step response. Compared with the traditional PID, the overshoot of the fuzzy self-adaptive PID algorithm decreases by 20.3%; the response speed is increased by 33.33%. A prototype of the belt drive system is developed, and the result of the algorithm verification experiment shows that the experimental data is basically consistent with the simulation data, the error controlled within 8%. Research provide theoretical and experimental bases for improving the position accuracy and robustness of the belt drive system.

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The datasets supporting the conclusion of this article are included within the article.

References

  1. Statkic S, Jeftenic IB, Bebic MZ et al (2019) Reliability assessment of the single motor drive of the belt conveyor on Drmno open-pit mine. Int J Electr Power Energy Syst 113(DEC):393–402. https://doi.org/10.1016/j.ijepes.2019.05.062

    Article  Google Scholar 

  2. Cheng PY, Chen PJ, Lin YT (2013) Small mechanical press with double-axis servo system for forming of small metal products[J]. Int J Adv Manuf Technol 68(9-12):2371–2381. https://doi.org/10.1007/s00170-013-4851-y

    Article  Google Scholar 

  3. He D, Liu X, Zhong B (2020) Sustainable belt conveyor operation by active speed control [J]. Measurement 154:107458. https://doi.org/10.1016/j.measurement.2019.107458

    Article  Google Scholar 

  4. Feng JB (2021) Energy saving application of frequency control technology in belt conveyor. Mechanical Research & Application 34(1):142–144. https://doi.org/10.16576/j.cnki.1007-4414.2021.01.044

    Article  Google Scholar 

  5. He GJ (2020) Control strategy of speed-regulating type magnetic coupler for mining multi-motor driving belt conveyor. Coal Mine Machinery 41(8):180–182. https://doi.org/10.13436/j.mkjx.202008059

    Article  Google Scholar 

  6. Masaki MS, Zhang L, Xia X (2018) A design approach for multiple drive belt conveyors minimizing life cycle costs[J]. J Clean Prod 201(PT.1-1166):526–541. https://doi.org/10.1016/j.jclepro.2018.08.040

    Article  Google Scholar 

  7. Zhan L, Kai Z (2013) Adaptive fuzzy sliding mode control for a robotic aircraft flexible tooling system[J]. Int J Adv Manuf Technol 69(5-8):1469–1481. https://doi.org/10.1007/s00170-013-5123-6

    Article  Google Scholar 

  8. Gong M, Xu YH, Li L (2019) Application of intermediate drive technology in main well belt conveyor. Coal Mine Machinery 40(7):146–148. https://doi.org/10.13436/j.mkjx.201907049

    Article  Google Scholar 

  9. Huang ZH, Wang SB (2017) Driving control strategy of intermediate unloading long distance belt conveyor. Industry and Mine Automation 43(7):48–52. https://doi.org/10.13272/j.issn.1671-251x.2017.07.010

    Article  Google Scholar 

  10. Hsieh MF, Yao WS, Chiang CR (2007) Modeling and synchronous control of a single-axis stage driven by dual mechanically-coupled parallel ball screws. Int J Adv Manuf Technol 34(9-10):933–943. https://doi.org/10.1007/s00170-007-1135-4

    Article  Google Scholar 

  11. Huang HH, Yan M, Wang W (2020) Optimization analysis of ultra-long distance belt conveyor soft start with CST. Coal Mine Machinery 41(10):119–122. https://doi.org/10.13436/j.mkjx.202010039

    Article  Google Scholar 

  12. Etin O, Dalcal A, Temurta F (2020) A comparative study on parameters estimation of squirrel cage induction motors using neural networks with unmemorized training–ScienceDirect. Engineering Science and Technology, an International Journal 23(5):1126–1133. https://doi.org/10.1016/j.jestch.2020.03.011

    Article  Google Scholar 

  13. Li B, Tian X, Zhang M (2019) Thermal error modeling of machine tool spindle based on the improved algorithm optimized BP neural network. Int J Adv Manuf Technol 105:105(9)–101505. https://doi.org/10.1007/s00170-019-04375-w

    Article  Google Scholar 

  14. Liu YC, Laghrouche S, N'Diaye A, Cirrincione M (2020) Hermite neural network-based second-order sliding-mode control of synchronous reluctance motor drive systems. Journal of the Franklin Institute 358(1). https://doi.org/10.1016/j.jfranklin.2020.10.029

  15. Jin JL, Wang YL, Zhu YQ (2018) Fuzzy parameter adaptive PID control of brushless DC motors. Control Engineering of China 25(5):915–919. https://doi.org/10.14107/j.cnki.kzgc.151090

    Article  Google Scholar 

  16. Choi H, Kim Y (2015) Implementation of evolutionary fuzzy PID speed controller for PM synchronous motor. IEEE Transactions on Industrial Informatics 11(2):540–547. https://doi.org/10.1109/TII.2013.2284561

    Article  Google Scholar 

  17. Chen HL (2019) Design of belt conveyor control system based on fuzzy PID algorithm. Coal MineMachinery 40(12):15–17. https://doi.org/10.13436/j.mkjx.201912006

    Article  Google Scholar 

  18. Maniexxo V, Carbonaro A (2000) An ants heuristic for the frequency assignment problem. Futur Gener Comput Syst 16(9):927–935. https://doi.org/10.1016/S0167-739X(00)00046-7

    Article  Google Scholar 

  19. Lee ZJ, Lee CY, Su SF (2002) An immunity-based ant colony optimization algorithm for solving weapon -target assignment problem. Appl Soft Comput 2(1):39–47. https://doi.org/10.1016/S1568-4946(02)00027-3

    Article  Google Scholar 

  20. Kim S, Park E, Jung S et al (2016) Optimal design of reformed auxiliary teeth for reducing end detent force of stationary discontinuous armature PMLSM. IEEE Trans Appl Supercond 26(4):1–5. https://doi.org/10.1109/TASC.2016.2527725

    Article  Google Scholar 

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Acknowledgements

Thanks are due to Dr. Ni for assistance with the experiments and to Dr. Zhao for valuable discussion.

Funding

This work was supported by the National Natural Science Foundation of China (Grant No. 51405419), Natural Science Foundation of the Jiangsu Higher Education Institutions of China (Grant No. 18KJB460029), and Yancheng Institute of Technology Training Program of Innovation and Entrepreneurship for Undergraduates (Grant No. 2020105).

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Authors and Affiliations

  1. School of Automotive Engineering, Yancheng Institute of Technology, Yancheng, 224051, Jiangsu, China

    Wei Liu, Ping Wan, Jin Cheng, Yongheng Ma & Cheng Jing

  2. Jiangsu Coastal Institute of New Energy Vehicle, Yancheng, 224051, Jiangsu, China

    Wei Liu

Authors
  1. Wei Liu
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  2. Ping Wan
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  3. Jin Cheng
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  4. Yongheng Ma
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  5. Cheng Jing
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Contributions

Investigation, methodology, project administration, supervision, and writing-review and editing, Wei Liu; investigation, methodology, validation, and writing-original draft, Ping Wan; investigation, Jin Cheng; data curation, Cheng Jing; and software, Yongheng Ma.

Corresponding author

Correspondence to Ping Wan.

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This article is part of the Topical Collection: New Intelligent Manufacturing Technologies through the Integration of Industry 4.0 and Advanced Manufacturing.

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Liu, W., Wan, P., Cheng, J. et al. High-precision position control of belt drive system based on OPC communication. Int J Adv Manuf Technol 122, 1–10 (2022). https://doi.org/10.1007/s00170-021-07859-w

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