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Acceleration Harmonic Estimation and Suppression for Hydraulic Load Simulator Based on Artificial Bee Colony with Chaotic Search Strategy.

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Title: Acceleration Harmonic Estimation and Suppression for Hydraulic Load Simulator Based on Artificial Bee Colony with Chaotic Search Strategy.
Authors: Zhenshuai Wan1,2 wanzhenshuai@haut.edu.cn, Longwang Yue2, Yanfeng Wang2, Pu Zhao2
Source: Journal of Mechanical Engineering / Strojniški Vestnik. 2024, Vol. 70 Issue 11/12, p531-542. 12p.
Subjects: Bee behavior, Division of labor, Bees, Nectar, Problem solving, Pollinators
Abstract: This paper presents a new hybrid algorithm based on artificial bee colony (ABC) and chaotic search strategy (CSS), known as ABC-CSS to solve the harmonic estimation problems in the case of time varying acceleration response signal. The ABC algorithm simulates the intelligent behavior of bees in nature to find high-quality nectar sources according to different divisions of labor. Aiming at the lack of diversity, poor global and local search ability, as well as slow convergence speed of ABC, an improved ABC based on CSS is proposed. The algorithm generates new neighborhood points by the transformation of chaotic and decision variables by carrier mapping, which provides a broader search space and better location of nectar sources for bees and recruited observation bees, and enhances the diversity of bee colonies. At the same time, the investigation of a local honey bee search better solves the algorithm problem of the local minimum and improves the convergence property of the ABC. Simulation and experimental studies are conducted to validate the superiority of the proposed ABC-CSS in harmonic estimation. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:This paper presents a new hybrid algorithm based on artificial bee colony (ABC) and chaotic search strategy (CSS), known as ABC-CSS to solve the harmonic estimation problems in the case of time varying acceleration response signal. The ABC algorithm simulates the intelligent behavior of bees in nature to find high-quality nectar sources according to different divisions of labor. Aiming at the lack of diversity, poor global and local search ability, as well as slow convergence speed of ABC, an improved ABC based on CSS is proposed. The algorithm generates new neighborhood points by the transformation of chaotic and decision variables by carrier mapping, which provides a broader search space and better location of nectar sources for bees and recruited observation bees, and enhances the diversity of bee colonies. At the same time, the investigation of a local honey bee search better solves the algorithm problem of the local minimum and improves the convergence property of the ABC. Simulation and experimental studies are conducted to validate the superiority of the proposed ABC-CSS in harmonic estimation. [ABSTRACT FROM AUTHOR]
ISSN:00392480
DOI:10.5545/sv-jme.2024.1047