| Summary: | Flexible plates are widely used in engineering and the industry, primarily due to the lightweight nature compared to rigid counterparts. These structures offer benefits such as cost savings, lower energy consumptions and improved operational safety. However, a notable drawback is that flexible structures are vulnerable to unwanted vibrations, which can cause structural damages. Hence, the development of specialized models are essential to effectively addressing this challenge. Researchers have devised various approaches to suppress unwanted vibrations, with contemporary studies often employing system identification techniques utilizing swarm intelligence algorithms to construct dynamic models of flexible structures. Therefore, this research employs the potent mayfly algorithm (MA), known for its effectiveness in optimization tasks. The developed models using MA were then compared with traditional approach known as recursive least square (RLS) through a comparative analysis. The outcome reveals that RLS exhibited the lowest mean square error (MSE) at 3.7392 × 10−6, while MA had an MSE of 5.5185 × 10−6. Yet, MA adeptly depicted the characteristics of the system, outperforming the RLS in these validation by indicating a 95% confidence level in the correlation test and exhibiting robust stability in the pole-zero diagram. Consequently, MA serves as a fitting algorithm to accurately depict the real behaviour of the flexible plate structure. © 2024, Semarak Ilmu Publishing. All rights reserved.
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