Multiobjective synchronization of coupled systems.
Multiobjective synchronization of coupled systems.
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DOI：
10.1063/1.3595701
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发表时间：
2011-06
期刊：
影响因子：
2.9
通讯作者：
Yang Tang;Zidong Wang;W. K. Wong;J. Kurths;Jian-an Fang
中科院分区：
文献类型：
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作者：
Yang Tang;Zidong Wang;W. K. Wong;J. Kurths;Jian-an Fang
本文研究了混沌系统的多目标同步问题，特别是同时最小化控制代价和收敛速度的优化问题。耦合形式和耦合强度的优化改进的多目标进化方法，包括一个混合染色体表示。混合编码方案结合了二进制表示和真实的数表示。通过将多目标同步问题转化为多目标约束问题，考虑了耦合形式上的约束。此外，通过混沌和超混沌状态下的Rössler系统和延迟混沌神经网络，分析和验证了自适应学习方法和非支配排序遗传算法II的性能以及所提方法的有效性和贡献.
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.