IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i23p4819-d1290547.html
   My bibliography  Save this article

Working Performance Improvement of a Novel Independent Metering Valve System by Using a Neural Network-Fractional Order-Proportional-Integral-Derivative Controller

Author

Listed:
  • Thanh Ha Nguyen

    (School of Mechanical and Automotive Engineering, University of Ulsan, 93 Deahak-ro, Nam-gu, Ulsan 44610, Republic of Korea)

  • Tri Cuong Do

    (School of Mechanical and Automotive Engineering, University of Ulsan, 93 Deahak-ro, Nam-gu, Ulsan 44610, Republic of Korea
    College of Technology and Design, University of Economics Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam)

  • Van Du Phan

    (School of Engineering and Technology, Vinh University, Vinh, Nghe An 43100, Vietnam)

  • Kyoung Kwan Ahn

    (School of Mechanical and Automotive Engineering, University of Ulsan, 93 Deahak-ro, Nam-gu, Ulsan 44610, Republic of Korea)

Abstract

In recent years, reducing the energy consumption in a hydraulic excavator has received deep attention in many studies. The implementation of the novel independent metering valve system (NIMV) has emerged as a promising solution in this regard. However, external factors such as noise, throttling loss, and leakage have negative influences on the tracking precision and energy saving in the NIMV system. In this paper, a novel control method, simple but effective, called a neural network-fractional order-proportional-integral-derivative controller is developed for the NIMV system. In detail, the fractional order-proportional-integral-derivative (FOPID) controller is used to improve the precision, stability, and fast response of the control system due to the inclusion of non-integer orders in the proportional, integral, and derivative terms. Along with that, the auto-tuning algorithm of the neural network controller is applied for adjusting five parameters in the FOPID controller under noise, throttling loss, and leakage. In addition, the proposed controller alleviates the amount of calculation for the system by using model-free control. To verify the effectiveness of the proposed controller, the simulation and experiment are conducted on the AMESim/MATLAB and a real test bench. As a result, the proposed controller not only operates the NIMV system accurately in the target trajectory but also reduces energy consumption, saving up 23.33% and 29.25% compared to FOPID and PID in the experimental platform, respectively.

Suggested Citation

  • Thanh Ha Nguyen & Tri Cuong Do & Van Du Phan & Kyoung Kwan Ahn, 2023. "Working Performance Improvement of a Novel Independent Metering Valve System by Using a Neural Network-Fractional Order-Proportional-Integral-Derivative Controller," Mathematics, MDPI, vol. 11(23), pages 1-21, November.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:23:p:4819-:d:1290547
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/23/4819/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/23/4819/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chen, Qihuai & Lin, Tianliang & Ren, Haoling & Fu, Shengjie, 2019. "Novel potential energy regeneration systems for hybrid hydraulic excavators," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 163(C), pages 130-145.
    2. Do, Tri Cuong & Dinh, Truong Quang & Yu, Yingxiao & Ahn, Kyoung Kwan, 2023. "Innovative powertrain and advanced energy management strategy for hybrid hydraulic excavators," Energy, Elsevier, vol. 282(C).
    3. Manh Hung Nguyen & Kyoung Kwan Ahn, 2023. "Output Feedback Robust Tracking Control for a Variable-Speed Pump-Controlled Hydraulic System Subject to Mismatched Uncertainties," Mathematics, MDPI, vol. 11(8), pages 1-20, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jiansong Li & Jiyun Zhao & Xiaochun Zhang, 2020. "A Novel Energy Recovery System Integrating Flywheel and Flow Regeneration for a Hydraulic Excavator Boom System," Energies, MDPI, vol. 13(2), pages 1-25, January.
    2. Van-Hien Nguyen & Tri Cuong Do & Kyoung-Kwan Ahn, 2024. "Implementing PSO-LSTM-GRU Hybrid Neural Networks for Enhanced Control and Energy Efficiency of Excavator Cylinder Displacement," Mathematics, MDPI, vol. 12(20), pages 1-21, October.
    3. Do, Tri Cuong & Dang, Tri Dung & Dinh, Truong Quang & Ahn, Kyoung Kwan, 2021. "Developments in energy regeneration technologies for hydraulic excavators: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    4. Manh Hung Nguyen & Kyoung Kwan Ahn, 2023. "Extended Sliding Mode Observer-Based Output Feedback Control for Motion Tracking of Electro-Hydrostatic Actuators," Mathematics, MDPI, vol. 11(20), pages 1-19, October.
    5. Liu, Huanlong & Chen, Guanpeng & Xie, Chixin & Li, Dafa & Wang, Jiawei & Li, Shun, 2020. "Research on energy-saving characteristics of battery-powered electric-hydrostatic hydraulic hybrid rail vehicles," Energy, Elsevier, vol. 205(C).
    6. Hyukjoon Kwon & Monika Ivantysynova, 2020. "System Characteristics Analysis for Energy Management of Power-Split Hydraulic Hybrids," Energies, MDPI, vol. 13(7), pages 1-23, April.
    7. Lin, Tianliang & Lin, Yuanzheng & Ren, Haoling & Chen, Haibin & Li, Zhongshen & Chen, Qihuai, 2021. "A double variable control load sensing system for electric hydraulic excavator," Energy, Elsevier, vol. 223(C).
    8. Kwon, Hyukjoon & Ivantysynova, Monika, 2021. "Experimental and theoretical studies on energy characteristics of hydraulic hybrids for thermal management," Energy, Elsevier, vol. 223(C).
    9. Lukasz Stawinski & Jakub Zaczynski & Adrian Morawiec & Justyna Skowronska & Andrzej Kosucki, 2021. "Energy Consumption Structure and Its Improvement of Low-Lifting Capacity Scissor Lift," Energies, MDPI, vol. 14(5), pages 1-14, March.
    10. Tan, Lisha & He, Xiangyu & Xiao, Guangxin & Jiang, Mengjun & Yuan, Yulin, 2022. "Design and energy analysis of novel hydraulic regenerative potential energy systems," Energy, Elsevier, vol. 249(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:11:y:2023:i:23:p:4819-:d:1290547. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.