IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i5p1145-d1080181.html
   My bibliography  Save this article

Intelligent Adaptive PID Control for the Shaft Speed of a Marine Electric Propulsion System Based on the Evidential Reasoning Rule

Author

Listed:
  • Xuelin Zhang

    (School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China)

  • Xiaobin Xu

    (School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China)

  • Xiaojian Xu

    (China Waterborne Transport Research Institute, Beijing 100088, China)

  • Pingzhi Hou

    (School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China)

  • Haibo Gao

    (School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, China)

  • Feng Ma

    (Smart Waterway Co., Ltd., Nanjing 210028, China)

Abstract

To precisely and timely control the shaft speed for a marine electric propulsion system under normal sea conditions, a new shaft speed control technique combining the evidential reasoning rule with the traditional PID controller was proposed in this study. First, an intelligent adaptive PID controller based on the evidential reasoning rule was designed for a marine electric propulsion system to obtain the PID parameters K P , K I , and K D . Then, a local iterative optimization strategy for model parameters was proposed. Furthermore, the parameters of the adaptive PID controller model were optimized in real time by using the sequential linear programming algorithm, which enabled the adaptive adjustment of K P , K I , and K D . Finally, the performance of the adaptive PID controller regarding the shaft speed control was compared with that of other controllers. The results showed that the adaptive PID controller designed in this study had better control performance, and the shaft speed control method based on the adaptive PID controller could better control the shaft speed of the marine electric propulsion system.

Suggested Citation

  • Xuelin Zhang & Xiaobin Xu & Xiaojian Xu & Pingzhi Hou & Haibo Gao & Feng Ma, 2023. "Intelligent Adaptive PID Control for the Shaft Speed of a Marine Electric Propulsion System Based on the Evidential Reasoning Rule," Mathematics, MDPI, vol. 11(5), pages 1-23, February.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:5:p:1145-:d:1080181
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/5/1145/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/5/1145/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Huu Khoa Tran & Juing-Shian Chiou & Viet-Hung Dang, 2020. "New Fusion Algorithm-Reinforced Pilot Control for an Agricultural Tricopter UAV," Mathematics, MDPI, vol. 8(9), pages 1-16, September.
    2. Mikulas Huba & Damir Vrancic, 2022. "Tuning of PID Control for the Double Integrator Plus Dead Time Model by Modified Real Dominant Pole and Performance Portrait Methods," Mathematics, MDPI, vol. 10(6), pages 1-25, March.
    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. Qi Liu & Hong Lu & Heisei Yonezawa & Ansei Yonezawa & Itsuro Kajiwara & Ben Wang, 2023. "Grey-Wolf-Optimization-Algorithm-Based Tuned P-PI Cascade Controller for Dual-Ball-Screw Feed Drive Systems," Mathematics, MDPI, vol. 11(10), pages 1-29, May.

    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. Qi Liu & Hong Lu & Heisei Yonezawa & Ansei Yonezawa & Itsuro Kajiwara & Ben Wang, 2023. "Grey-Wolf-Optimization-Algorithm-Based Tuned P-PI Cascade Controller for Dual-Ball-Screw Feed Drive Systems," Mathematics, MDPI, vol. 11(10), pages 1-29, May.

    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:5:p:1145-:d:1080181. 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.