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Parameter estimation of fractional-order system with improved Archimedes optimization algorithm
Chen, Yinbin1; Yang, Renhuan1; Yang, Xiuzeng2; Yang, Renyu3; Huang, Qidong1; Chen, Guilian1; Zhang, Ling4; Wei, Mengyu5; Zhou, Yongqiang6
2024-08-27
Source PublicationInternational Journal of Modern Physics C
ISSN0129-1831
Abstract

In this paper, aiming at the problems of slow estimation speed and low estimation precision of traditional fractional-order system (FOS) parameter estimation method, an improved Archimedes optimization algorithm (IAOA) is proposed to calculate the optimal value. By establishing the parameter estimation model and the cost function, the parameter estimation problem is formulated as an optimization problem. As opposed to the Archimedes optimization algorithm (AOA), the IAOA introduces three improvements: leadership behavior, levy °ight behavior and a new adaptive strategy. This paper veri¯es the performance of the IAOA by selecting 10 classic test functions. IAOA is applied to the parameter estimation problem of fractional-order uni¯ed system to verify the accuracy and feasibility of the algorithm. The simulation results prove that the IAOA has better global optimization ability and estimation accuracy than the original algorithm.

KeywordFractional-order System Improved Archimedes Optimization Algorithm Intelligent Optimization Algorithm Parameter Estimation
DOI10.1142/S0129183124501973
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science ; Physics
WOS SubjectComputer Science, Interdisciplinary Applications ; Physics, Mathematical
WOS IDWOS:001295856200001
PublisherWORLD SCIENTIFIC PUBL CO PTE LTD, 5 TOH TUCK LINK, SINGAPORE 596224, SINGAPORE
Scopus ID2-s2.0-85202047038
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Document TypeJournal article
CollectionFaculty of Science and Technology
Corresponding AuthorChen, Yinbin; Yang, Xiuzeng
Affiliation1.College of Information Science and Technology, Jinan University, Guangzhou, 510632, China
2.Department of Physics and Electronic Engineering, Guangxi Normal University for Nationalities, Chongzuo 532200, P. R. China
3.The School of Information Science, Guangdong University of Finance Economics, Guangzhou, 510320, China
4.Experiment and Training Center, Guangzhou Vocational College of Technology & Business, Guangzhou, 510632, China
5.Faculty of Science and Technology, University of Macau, Macau 999078, P. R. China
6.School of Electronics and Information Engineering, Wuyi University, Jiangmen 529020, P. R. China
Recommended Citation
GB/T 7714
Chen, Yinbin,Yang, Renhuan,Yang, Xiuzeng,et al. Parameter estimation of fractional-order system with improved Archimedes optimization algorithm[J]. International Journal of Modern Physics C, 2024.
APA Chen, Yinbin., Yang, Renhuan., Yang, Xiuzeng., Yang, Renyu., Huang, Qidong., Chen, Guilian., Zhang, Ling., Wei, Mengyu., & Zhou, Yongqiang (2024). Parameter estimation of fractional-order system with improved Archimedes optimization algorithm. International Journal of Modern Physics C.
MLA Chen, Yinbin,et al."Parameter estimation of fractional-order system with improved Archimedes optimization algorithm".International Journal of Modern Physics C (2024).
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