Efficient Time-Delay System Optimization with Auto-Configured Metaheuristics
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F23%3A63573979" target="_blank" >RIV/70883521:28140/23:63573979 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10394087&tag=1" target="_blank" >https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10394087&tag=1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SMC53992.2023.10394087" target="_blank" >10.1109/SMC53992.2023.10394087</a>
Alternative languages
Result language
angličtina
Original language name
Efficient Time-Delay System Optimization with Auto-Configured Metaheuristics
Original language description
This paper presents an experimental study that compares the performance of four selected metaheuristic algorithms for optimizing a time delay system model. Time delay system models are complex and challenging to optimize due to their inherent characteristics, such as non-linearity, multimodality, and constraints. The study includes an explanation of the choice and core functionality of the selected algorithms, which are both baseline and state-of-the-art variants of self-organizing migrating algorithm (SOMA), state-of-the-art variant from the Success-History-based Adaptive Differential Evolution family of algorithms, with emphasis on diverse search (DISH algorithm), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. The hyperparameters of the metaheuristic algorithms were set using the iRace automatic algorithm configuration framework. The paper emphasizes the importance of metaheuristic algorithms in control engineering for time-delay systems to develop more effective and efficient control strategies and precise model identifications. The experimental results highlight the effectiveness of the state- of-the-art algorithms with specific adaptive mechanisms like population organization process, diverse search and adaptation mechanisms ensuring a gradual transition from exploration to exploitation. Overall, this study contributes to understanding the challenges and advantages of using metaheuristic algorithms in control engineering for time delay systems. The results provide valuable insights into the performance of modern metaheuristic algorithms and can help guide the selection of appropriate adaptive mechanisms of metaheuristics.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GF21-45465L" target="_blank" >GF21-45465L: Metaheuristic-based parametric optimization of time-delay models and control systems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
ISBN
979-8-3503-3703-7
ISSN
1062-922X
e-ISSN
2577-1655
Number of pages
6
Pages from-to
1084-1089
Publisher name
IEEE
Place of publication
New Jersey, Piscataway
Event location
Honolulu
Event date
Oct 1, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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