IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i2p459-d309994.html
   My bibliography  Save this article

Proportional–Integral–Derivative Controller Design Using an Advanced Lévy-Flight Salp Swarm Algorithm for Hydraulic Systems

Author

Listed:
  • Yuqi Fan

    (Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080, China)

  • Junpeng Shao

    (Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080, China)

  • Guitao Sun

    (Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080, China)

  • Xuan Shao

    (Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080, China)

Abstract

To improve the control ability of proportional–integral–derivative (PID) controllers and increase the stability of force actuator systems, this paper introduces a PID controller based on the self-growing lévy-flight salp swarm algorithm (SG-LSSA) in the force actuator system. First, the force actuator system model was built, and the transfer function model was obtained by the identification of system parameters identifying. Second, the SG-LSSA was proposed and used to test ten benchmark functions. Then, SG-LSSA-PID, whose parameters were tuned by SG-LSSA, was applied to the electro-hydraulic force actuator system to suppress interference signals. Finally, the temporal response characteristic and the frequency response characteristic were studied and compared with different algorithms. Ten benchmark function experiments indicate that SG-LSSA has a superior convergence speed and perfect optimization capability. The system performance results demonstrate that the electro-hydraulic force actuator system utilized the SG-LSSA-PID controller has a remarkable capability to maintain the stability and robustness under unknown interference signals.

Suggested Citation

  • Yuqi Fan & Junpeng Shao & Guitao Sun & Xuan Shao, 2020. "Proportional–Integral–Derivative Controller Design Using an Advanced Lévy-Flight Salp Swarm Algorithm for Hydraulic Systems," Energies, MDPI, vol. 13(2), pages 1-20, January.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:2:p:459-:d:309994
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/2/459/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/2/459/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jiyang Wang & Yuyang Gao & Xuejun Chen, 2018. "A Novel Hybrid Interval Prediction Approach Based on Modified Lower Upper Bound Estimation in Combination with Multi-Objective Salp Swarm Algorithm for Short-Term Load Forecasting," Energies, MDPI, vol. 11(6), pages 1-30, June.
    2. Yang Yang & Guangzheng Li & Quanrang Zhang, 2018. "A Pressure-Coordinated Control for Vehicle Electro-Hydraulic Braking Systems," Energies, MDPI, vol. 11(9), pages 1-21, September.
    3. Minh Tri Nguyen & Tri Dung Dang & Kyoung Kwan Ahn, 2019. "Application of Electro-Hydraulic Actuator System to Control Continuously Variable Transmission in Wind Energy Converter," Energies, MDPI, vol. 12(13), pages 1-19, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Çetin, Gürcan & Özkaraca, Osman & Keçebaş, Ali, 2021. "Development of PID based control strategy in maximum exergy efficiency of a geothermal power plant," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).

    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. Lifang Zhang & Jianzhou Wang & Zhenkun Liu, 2023. "Power grid operation optimization and forecasting using a combined forecasting system," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 124-153, January.
    2. Guishan Yan & Zhenlin Jin & Mingkun Yang & Bing Yao, 2021. "The Thermal Balance Temperature Field of the Electro-Hydraulic Servo Pump Control System," Energies, MDPI, vol. 14(5), pages 1-24, March.
    3. Tawhid, Mohamed A. & Ibrahim, Abdelmonem M., 2022. "Improved salp swarm algorithm combined with chaos," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 113-148.
    4. Wang, Jianzhou & Gao, Jialu & Wei, Danxiang, 2022. "Electric load prediction based on a novel combined interval forecasting system," Applied Energy, Elsevier, vol. 322(C).
    5. Cong-Trang Nguyen & Thanh Long Duong & Minh Quan Duong & Duc Tung Le, 2020. "Chattering-Free Single-Phase Robustness Sliding Mode Controller for Mismatched Uncertain Interconnected Systems with Unknown Time-Varying Delays," Energies, MDPI, vol. 13(1), pages 1-27, January.
    6. Zielinski, Michał & Myszkowski, Adam & Pelic, Marcin & Staniek, Roman, 2022. "Low-speed radial piston pump as an effective alternative power transmission for small hydropower plants," Renewable Energy, Elsevier, vol. 182(C), pages 1012-1027.
    7. Niu, Xinsong & Wang, Jiyang, 2019. "A combined model based on data preprocessing strategy and multi-objective optimization algorithm for short-term wind speed forecasting," Applied Energy, Elsevier, vol. 241(C), pages 519-539.
    8. Zhang, Wenyu & Zhang, Lifang & Wang, Jianzhou & Niu, Xinsong, 2020. "Hybrid system based on a multi-objective optimization and kernel approximation for multi-scale wind speed forecasting," Applied Energy, Elsevier, vol. 277(C).
    9. Tongxiang Liu & Yu Jin & Yuyang Gao, 2019. "A New Hybrid Approach for Short-Term Electric Load Forecasting Applying Support Vector Machine with Ensemble Empirical Mode Decomposition and Whale Optimization," Energies, MDPI, vol. 12(8), pages 1-20, April.
    10. Wang, Ying & Wang, Jianzhou & Li, Zhiwu & Yang, Hufang & Li, Hongmin, 2021. "Design of a combined system based on two-stage data preprocessing and multi-objective optimization for wind speed prediction," Energy, Elsevier, vol. 231(C).
    11. Yang Yang & Yundong He & Zhong Yang & Chunyun Fu & Zhipeng Cong, 2020. "Torque Coordination Control of an Electro-Hydraulic Composite Brake System During Mode Switching Based on Braking Intention," Energies, MDPI, vol. 13(8), pages 1-19, April.
    12. Yechi Zhang & Jianzhou Wang & Haiyan Lu, 2019. "Research and Application of a Novel Combined Model Based on Multiobjective Optimization for Multistep-Ahead Electric Load Forecasting," Energies, MDPI, vol. 12(10), pages 1-27, May.
    13. Elattar, Ehab E. & ElSayed, Salah K., 2020. "Probabilistic energy management with emission of renewable micro-grids including storage devices based on efficient salp swarm algorithm," Renewable Energy, Elsevier, vol. 153(C), pages 23-35.
    14. Subbulakshmi, A. & Verma, Mohit & Keerthana, M. & Sasmal, Saptarshi & Harikrishna, P. & Kapuria, Santosh, 2022. "Recent advances in experimental and numerical methods for dynamic analysis of floating offshore wind turbines — An integrated review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 164(C).
    15. Mohamed H. Hassan & Salah Kamel & José Luís Domínguez-García & Mohamed F. El-Naggar, 2022. "MSSA-DEED: A Multi-Objective Salp Swarm Algorithm for Solving Dynamic Economic Emission Dispatch Problems," Sustainability, MDPI, vol. 14(15), pages 1-23, August.
    16. Zhou, Qingguo & Wang, Chen & Zhang, Gaofeng, 2019. "Hybrid forecasting system based on an optimal model selection strategy for different wind speed forecasting problems," Applied Energy, Elsevier, vol. 250(C), pages 1559-1580.
    17. Mingkun Yang & Gexin Chen & Jianxin Lu & Cong Yu & Guishan Yan & Chao Ai & Yanwen Li, 2021. "Research on Energy Transmission Mechanism of the Electro-Hydraulic Servo Pump Control System," Energies, MDPI, vol. 14(16), pages 1-17, August.
    18. Sukjoon Oh & Chul Kim & Joonghyeok Heo & Sung Lok Do & Kee Han Kim, 2020. "Heating Performance Analysis for Short-Term Energy Monitoring and Prediction Using Multi-Family Residential Energy Consumption Data," Energies, MDPI, vol. 13(12), pages 1-24, June.
    19. Wang, Jianzhou & Wang, Shiqi & Yang, Wendong, 2019. "A novel non-linear combination system for short-term wind speed forecast," Renewable Energy, Elsevier, vol. 143(C), pages 1172-1192.
    20. Liu, Zhenkun & Jiang, Ping & Zhang, Lifang & Niu, Xinsong, 2020. "A combined forecasting model for time series: Application to short-term wind speed forecasting," Applied Energy, Elsevier, vol. 259(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:jeners:v:13:y:2020:i:2:p:459-:d:309994. 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.