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Application of Fuzzy PID Based on Stray Lion Swarm Optimization Algorithm in Overhead Crane System Control

Author

Listed:
  • Jie Fu

    (Rail Transit Department, Zhejiang Institute of Communications, Hangzhou 311112, China)

  • Jian Liu

    (College of Information Engineering, Nanjing University of Finance and Economics, Nanjing 210023, China)

  • Dongkai Xie

    (Alibaba Cloud Intelligence Business Group, Alibaba Co., Ltd., Hangzhou 310024, China)

  • Zhe Sun

    (Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology), Nanjing University of Posts and Telecommunications, Nanjing 210023, China
    Post Big Data Technology and Application Engineering Research Center of Jiangsu Province, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

Abstract

To solve the problem of crane anti-swing, fuzzy PID is a common method. However, the parameter configuration of fuzzy PID requires a lot of time and effort from professionals. Based on this, we introduce the LSO algorithm and add the stray operator, which effectively improves its global search performance. By combining SLSO and fuzzy PID and comparing them with other methods, this paper confirms that even without the targeted optimization by professionals, the optimization algorithm can find the appropriate parameter configuration for fuzzy PID which can be effectively used in the crane anti-swing problem.

Suggested Citation

  • Jie Fu & Jian Liu & Dongkai Xie & Zhe Sun, 2023. "Application of Fuzzy PID Based on Stray Lion Swarm Optimization Algorithm in Overhead Crane System Control," Mathematics, MDPI, vol. 11(9), pages 1-18, May.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:9:p:2170-:d:1139764
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    References listed on IDEAS

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    1. Francisco J. Solis & Roger J.-B. Wets, 1981. "Minimization by Random Search Techniques," Mathematics of Operations Research, INFORMS, vol. 6(1), pages 19-30, February.
    2. Juan Garrido & Francisco Vázquez & Fernando Morilla, 2016. "Multivariable PID control by decoupling," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(5), pages 1054-1072, April.
    3. Wang, Nan & Wang, Dongxuan & Xing, Yazhou & Shao, Limin & Afzal, Sadegh, 2020. "Application of co-evolution RNA genetic algorithm for obtaining optimal parameters of SOFC model," Renewable Energy, Elsevier, vol. 150(C), pages 221-233.
    4. Ali, Tariq, 2016. "Optimal PID controller design through swarm intelligence algorithms for sun tracking systemAuthor-Name: Sabir, Mirza Muhammad," Applied Mathematics and Computation, Elsevier, vol. 274(C), pages 690-699.
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