Multiobjective synchronization of coupled systems

Yang Tang; Zidong Wang; Wai Keung Wong; Jürgen Kurths; Jian an Fang

doi:10.1063/1.3595701

Multiobjective synchronization of coupled systems

Yang Tang, Zidong Wang, Wai Keung Wong, Jürgen Kurths, Jian an Fang

Research output: Journal article publication › Journal article › Academic research › peer-review

51 Citations (Scopus)

Abstract

In this paper, multiobjective synchronization of chaotic systems is investigated by especially simultaneously minimizing optimization of control cost and convergence speed. The coupling form and coupling strength are optimized by an improved multiobjective evolutionary approach that includes a hybrid chromosome representation. The hybrid encoding scheme combines binary representation with real number representation. The constraints on the coupling form are also considered by converting the multiobjective synchronization into a multiobjective constraint problem. In addition, the performances of the adaptive learning method and non-dominated sorting genetic algorithm-II as well as the effectiveness and contributions of the proposed approach are analyzed and validated through the Rössler system in a chaotic or hyperchaotic regime and delayed chaotic neural networks.

Original language	English
Article number	025114
Journal	Chaos
Volume	21
Issue number	2
DOIs	https://doi.org/10.1063/1.3595701
Publication status	Published - 1 Jan 2011

ASJC Scopus subject areas

Statistical and Nonlinear Physics
Mathematical Physics
Physics and Astronomy(all)
Applied Mathematics

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10.1063/1.3595701

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AU - Wang, Zidong

AU - Wong, Wai Keung

AU - Kurths, Jürgen

AU - Fang, Jian an

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AB - In this paper, multiobjective synchronization of chaotic systems is investigated by especially simultaneously minimizing optimization of control cost and convergence speed. The coupling form and coupling strength are optimized by an improved multiobjective evolutionary approach that includes a hybrid chromosome representation. The hybrid encoding scheme combines binary representation with real number representation. The constraints on the coupling form are also considered by converting the multiobjective synchronization into a multiobjective constraint problem. In addition, the performances of the adaptive learning method and non-dominated sorting genetic algorithm-II as well as the effectiveness and contributions of the proposed approach are analyzed and validated through the Rössler system in a chaotic or hyperchaotic regime and delayed chaotic neural networks.

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Multiobjective synchronization of coupled systems

Abstract

ASJC Scopus subject areas

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