Identification of Chua’s chaotic circuit parameters using penguins search optimisation algorithm

Q2 Engineering
F. Maamri, S. Bououden, I. Boulkaibet
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引用次数: 1

Abstract

ABSTRACT In this paper, the Penguins Search optimisation (PeSOA) Algorithm is used to identify optimal control parameters of the Chua circuit. The PeSOA algorithm, which is one of the nature-inspired algorithms, is mainly based on the collaborative hunting concept of penguins. In this algorithm, each penguin individually starts its search process, then communicates its position and the number of fish found to his group. The main objective of this strategy is to synchronise dives among the group in order to achieve a global solution. In this paper, a PeSOA algorithm is adopted to explore the search space for locating the optimum intervals and identify the unknown Chua’s system parameters without any partial knowledge of the internal structure. The identified parameters, obtained by minimising the objective function between the estimated and the output values of the system, are used to obtain stable oscillations. The obtained results show that the PeSOA algorithm gives accurate results and the identified parameters produce a stable oscillation of Chua’s chaotic circuit.
用企鹅搜索优化算法辨识蔡氏混沌电路参数
摘要:本文采用企鹅搜索优化算法(PeSOA)识别蔡氏电路的最优控制参数。PeSOA算法是一种受自然启发的算法,主要基于企鹅的协同捕猎概念。在这个算法中,每只企鹅单独开始它的搜索过程,然后将它的位置和发现的鱼的数量传达给它的群体。这个策略的主要目标是在群体中同步潜水,以实现一个全局解决方案。本文采用PeSOA算法,在不了解系统内部结构的情况下,探索搜索空间,定位最优区间,识别未知的Chua系统参数。通过最小化系统的估计值和输出值之间的目标函数得到的识别参数用于获得稳定的振荡。结果表明,PeSOA算法给出了准确的结果,所识别的参数产生了蔡氏混沌电路的稳定振荡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cyber-Physical Systems
Cyber-Physical Systems Engineering-Computational Mechanics
CiteScore
3.10
自引率
0.00%
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