Multiobjective synchronization of coupled systems

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

Research output: Journal article publicationJournal articleAcademic researchpeer-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 languageEnglish
Article number025114
JournalChaos
Volume21
Issue number2
DOIs
Publication statusPublished - 1 Jan 2011

ASJC Scopus subject areas

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

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