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Wind Driven Butterfly Optimization Algorithm with Hybrid Mechanism Avoiding Natural Enemies for Global Optimization and PID Controller Design

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Abstract

This paper presents a Butterfly Optimization Algorithm (BOA) with a wind-driven mechanism for avoiding natural enemies known as WDBOA. To further balance the basic BOA algorithm's exploration and exploitation capabilities, the butterfly actions were divided into downwind and upwind states. The algorithm of exploration ability was improved with the wind, while the algorithm of exploitation ability was improved against the wind. Also, a mechanism of avoiding natural enemies based on Lévy flight was introduced for the purpose of enhancing its global searching ability. Aiming at improving the explorative performance at the initial stages and later stages, the fragrance generation method was modified. To evaluate the effectiveness of the suggested algorithm, a comparative study was done with six classical metaheuristic algorithms and three BOA variant optimization techniques on 18 benchmark functions. Further, the performance of the suggested technique in addressing some complicated problems in various dimensions was evaluated using CEC 2017 and CEC 2020. Finally, the WDBOA algorithm is used proportional-integral-derivative (PID) controller parameter optimization. Experimental results demonstrate that the WDBOA based PID controller has better control performance in comparison with other PID controllers tuned by the Genetic Algorithm (GA), Flower Pollination Algorithm (FPA), Cuckoo Search (CS) and BOA.

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Funding

This work was supported by National Natural Science Foundation of China under Grant U21A20464, 62066005. Project of the Guangxi Science and Technology under Grant No.ZL23014016.

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Authors and Affiliations

  1. College of Artificial Intelligence, Guangxi University for Nationalities, Nanning, 530006, China

    Yang He, Yongquan Zhou & Qifang Luo

  2. College of Electronic Information and Automation, Civil Aviation University of China, Tianjin, 300300, China

    Wu Deng

  3. Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Yongquan Zhou & Yuanfei Wei

  4. Guangxi Key Laboratories of Hybrid Computation and IC Design Analysis, Nanning, 530006, China

    Yang He, Yongquan Zhou & Qifang Luo

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  1. Yang He
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  4. Qifang Luo
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Contributions

YH Conceptualization, Methodology, Formal analysis, Investigation, Writing – original draft. YZ Conceptualization, Resources, Writing – review & editing, Supervision, Funding acquisition. YW Conceptualization, Writing – review & editing. QL: Conceptualization, Writing – review & editing. WD: Conceptualization, Writing – review & editing.

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Correspondence to Yongquan Zhou or Qifang Luo.

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All the work outlined in this paper is our own except where otherwise acknowledged and referenced. The work contained in the manuscript has not been previously published, in whole or part, and is not under consideration by any other journal. All authors are aware of and accept responsibility for the Manuscript. The authors declare that they have no conflicts of interest.

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He, Y., Zhou, Y., Wei, Y. et al. Wind Driven Butterfly Optimization Algorithm with Hybrid Mechanism Avoiding Natural Enemies for Global Optimization and PID Controller Design. J Bionic Eng 20, 2935–2972 (2023). https://doi.org/10.1007/s42235-023-00416-z

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