文献类型：期刊文献

英文题名：Towards efficient identification of fractional-order systems

作者：Liang, Chen[1];Chen, Mingke[1]

机构：[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China

年份：2024

卷号：525

外文期刊名：PHYSICS LETTERS A

收录：;EI(收录号：20243717033981);WOS:【SCI-EXPANDED(收录号:WOS:001315184600001)】；

基金：Declaration of competing interest The authors declare the following financial interests/personal rela-tionships which may be considered as potential competing interests: Chen Liang reports financial support was provided by East China Univer-sity of Science and Technology. Chen Liang reports a relationship with East China University of Science and Technology that includes: employ-ment. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

语种：英文

外文关键词：Fractional-order systems; System identification; Time step; Iteration time; Metaheuristic algorithms

摘要：This study focuses on the efficient identification of fractional-order chaotic systems, particularly under challenging conditions where the time step, iteration time, orders, parameters, initial values, and system structure are all unknown. Unlike previous work, our approach emphasizes the complexities introduced by the unknown time step and iteration time. We introduce a novel differential evolution (DE) variant, termed global and local search using success-history based parameter adaptation for differential evolution (GL-SHADE), to tackle this problem in both noiseless and noisy environments. Comprehensive simulations show that GL-SHADE outperforms other comparative algorithms by delivering both higher precision and faster convergence under these uncertain conditions, highlighting the potential of advanced DE techniques in complex system identification.