dc.contributor.author | Izci, Davut | |
dc.contributor.author | Rizk-Allah, Rizk M. | |
dc.contributor.author | Snášel, Václav | |
dc.contributor.author | Ekinci, Serdar | |
dc.contributor.author | Migdady, Hazem | |
dc.contributor.author | Daoud, Mohammad Sh. | |
dc.contributor.author | Altalhi, Maryam | |
dc.contributor.author | Abualigah, Laith | |
dc.date.accessioned | 2024-11-28T08:18:56Z | |
dc.date.available | 2024-11-28T08:18:56Z | |
dc.date.issued | 2024 | |
dc.identifier.citation | Electrical Engineering. 2024. | cs |
dc.identifier.issn | 0948-7921 | |
dc.identifier.issn | 1432-0487 | |
dc.identifier.uri | http://hdl.handle.net/10084/155360 | |
dc.description.abstract | The efficacy of automatic voltage regulator (AVR) systems is contingent on crucial parameters like voltage regulation, response time, stability, and efficiency. Integration of controllers with AVR systems facilitates centralized monitoring and regulation, enhancing voltage output efficiency. This study employs a modified sinh cosh optimizer (m-SCHO) and a modified time-domain metrics-based objective function to fine-tune a fractional-order proportional-integral-derivative with double derivative (FOPIDD2) controller tailored for AVR system control. The m-SCHO is strengthened with an adaptive local search mechanism and an experience-based perturbed learning strategy and enhances solution diversity and navigational efficacy, leading to improved optimization quality. This investigation illustrates the superior performance of the m-SCHO-based FOPIDD2 controller in addressing the multifaceted challenges of AVR control, surpassing other techniques in stability, speed of response, robustness, and efficiency. To validate the method's efficacy, a comparative analysis is conducted using existing controllers with various tuning algorithms. Results indicate that the proposed m-SCHO-based FOPIDD2 controller achieves superior performance metrics, showcasing its capability. The study extends its scope by considering nineteen different controllers reported in the literature for a comprehensive comparison which also exhibits the best stability, further affirming its effectiveness. | cs |
dc.language.iso | en | cs |
dc.publisher | Springer Nature | cs |
dc.relation.ispartofseries | Electrical Engineering | cs |
dc.relation.uri | https://doi.org/10.1007/s00202-024-02344-5 | cs |
dc.rights | Copyright © 2024, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature | cs |
dc.subject | optimization | cs |
dc.subject | sinh cosh optimizer | cs |
dc.subject | automatic voltage regulator | cs |
dc.subject | adaptive local search | cs |
dc.subject | experience-based perturbed learning | cs |
dc.title | Refined sinh cosh optimizer tuned controller design for enhanced stability of automatic voltage regulation | cs |
dc.type | article | cs |
dc.identifier.doi | 10.1007/s00202-024-02344-5 | |
dc.type.status | Peer-reviewed | cs |
dc.description.source | Web of Science | cs |
dc.identifier.wos | 001194701200002 | |