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

Author

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  • 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
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    References listed on IDEAS

    as
    1. 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).
    2. 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.
    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.
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