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Modelling of flexible beam based on ant colony optimization and cuckoo search algorithms


Citation

Ali, Siti Khadijah and Fadzilan, Mohamad Faisal and Shaari, Aida Nur Syafiqah and Hadi, Muhamad Sukri and Ting, Rickey Pek Eek and Mat Darus, Intan Zaurah (2021) Modelling of flexible beam based on ant colony optimization and cuckoo search algorithms. Journal of Vibroengineering, 23 (4). 810 - 822. ISSN 1392-8716; ESSN: 2538-8460

Abstract

Flexible beam structure is usually applied in various fields of engineering and industrial. There are few points of interest using flexible structure and one of the advantages is that its lighter compared to a rigid structure. Besides that, flexible beam also can save cost, reduce energy consumption, and improve operation safety. However, flexible beam structures are too sensitive and susceptible to with unwanted vibration that would cause damage or degradation to the structure system. Hence, to overcome the problem, appropriate modelling and controller for such systems should be developed. Currently, there are plenty of methods that have been developed by researchers to suppress undesired vibration. Based on previous studies, most researchers nowadays use system identification (SI) as a modelling technique to develop a dynamic model of flexible structure via swarm intelligence algorithm (SIA). Therefore, two type of algorithms was used in this work for modelling development of flexible beam structure, which are ant colony optimization (ACO) and cuckoo search algorithm (CSA). Based on the comparative results, CSA achieved the lowest mean square error (MSE) value of 6.1547×10-9 meanwhile ACO recorded a MSE of 1.0728×10-8. Moreover, CSA was deduced to be the best model for flexible beam structure because it achieved 95 % confidence level in correlation test and has excellent stability in pole-zero diagram system. Thus, CSA is a suitable algorithm to represent the real behavior of flexible beam structure in a system.


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Official URL or Download Paper: https://www.extrica.com/article/21730

Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.21595/jve.2020.21730
Publisher: Extrica
Keywords: Flexible beam; System identification; Ant colony optimization; Cuckoo search algorithm; Swarm intelligence algorithm
Depositing User: Ms. Nur Faseha Mohd Kadim
Date Deposited: 09 May 2023 01:31
Last Modified: 09 May 2023 01:31
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.21595/jve.2020.21730
URI: http://psasir.upm.edu.my/id/eprint/94225
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