Advanced control parameter optimization in DC motors and liquid level systems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10260613" target="_blank" >RIV/61989100:27240/25:10260613 - isvavai.cz</a>
Result on the web
<a href="https://www.nature.com/articles/s41598-025-85273-y" target="_blank" >https://www.nature.com/articles/s41598-025-85273-y</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41598-025-85273-y" target="_blank" >10.1038/s41598-025-85273-y</a>
Alternative languages
Result language
angličtina
Original language name
Advanced control parameter optimization in DC motors and liquid level systems
Original language description
In recent times, there has been notable progress in control systems across various industrial domains, necessitating effective management of dynamic systems for optimal functionality. A crucial research focus has emerged in optimizing control parameters to augment controller performance. Among the plethora of optimization algorithms, the mountain gazelle optimizer (MGO) stands out for its capacity to emulate the agile movements and behavioral strategies observed in mountain gazelles. This paper introduces a novel approach employing MGO to optimize control parameters in both a DC motor and three-tank liquid level systems. The fine-tuning of proportional-integral-derivative (PID) controller parameters using MGO achieves remarkable results, including a rise time of 0.0478 s, zero overshoot, and a settling time of 0.0841 s for the DC motor system. Similarly, the liquid level system demonstrates improved control with a rise time of 11.0424 s and a settling time of 60.6037 s. Comparative assessments with competitive algorithms, such as the grey wolf optimizer and particle swarm optimization, reveal MGO's superior performance. Furthermore, a new performance indicator, ZLG, is introduced to comprehensively evaluate control quality. The MGO-based approach consistently achieves lower ZLG values, showcasing its adaptability and robustness in dynamic system control and parameter optimization. By providing a dependable and efficient optimization methodology, this research contributes to advancing control systems, promoting stability, and enhancing efficiency across diverse industrial applications.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10700 - Other natural sciences
Result continuities
Project
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Continuities
O - Projekt operacniho programu
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Scientific Reports
ISSN
2045-2322
e-ISSN
2045-2322
Volume of the periodical
15
Issue of the periodical within the volume
1
Country of publishing house
GB - UNITED KINGDOM
Number of pages
16
Pages from-to
1-16
UT code for WoS article
001394990600043
EID of the result in the Scopus database
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