Optimal targeting of nonlinear chaotic systems using a novel evolutionary computing strategy

doi:10.1016/j.knosys.2016.06.019

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	Optimal targeting of nonlinear chaotic systems using a novel evolutionary computing strategy
	Wang, Yudong 1; Feng, Xiaoyi 2; Lyu, Xin 2; Li, Zhengyang 2; Liu, Bo2
	2016-09-01
发表期刊	KNOWLEDGE-BASED SYSTEMS
ISSN	0950-7051
卷号	107 页码:261-270
摘要	Control of chaotic systems to given targets is a subject of substantial and well-developed research issue in nonlinear science, which can be formulated as a class of multi-modal constrained numerical optimization problem with multi-dimensional decision variables. This investigation elucidates the feasibility of applying a novel population-based metaheuristics labeled here as Teaching-learning-based optimization to direct the orbits of discrete chaotic dynamical systems towards the desired target region. Several consecutive control steps of small bounded perturbations are made in the Teaching-learning-based optimization strategy to direct the chaotic series towards the optimal neighborhood of the desired target rapidly, where a conventional controller is effective for chaos control. Working with the dynamics of the well-known Henan as well as Ushio discrete chaotic systems, we assess the effectiveness and efficiency of the Teaching-learning-based optimization based optimal control technique, meanwhile the impacts of the core parameters on performances are also discussed. Furthermore, possible engineering applications of directing chaotic orbits are discussed. (C) 2016 Elsevier B.V. All rights reserved.
关键词	Chaos control Chaotic dynamics Optimization Computational intelligence Teaching-learning-based optimization
DOI	10.1016/j.knosys.2016.06.019
语种	英语
资助项目	National Natural Science Foundation of China[71101139] ; National Natural Science Foundation of China[71390331] ; National Natural Science Foundation of China[11272062] ; National Science Fund for Distinguished Young Scholars of China[61525304] ; Defense Industrial Technology Development Program
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000380595900020
出版者	ELSEVIER SCIENCE BV
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/23458
专题	系统科学研究所
通讯作者	Liu, Bo
作者单位	1.Sci & Technol Space Phys Lab, Beijing, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Wang, Yudong,Feng, Xiaoyi,Lyu, Xin,et al. Optimal targeting of nonlinear chaotic systems using a novel evolutionary computing strategy[J]. KNOWLEDGE-BASED SYSTEMS,2016,107:261-270.
APA	Wang, Yudong,Feng, Xiaoyi,Lyu, Xin,Li, Zhengyang,&Liu, Bo.(2016).Optimal targeting of nonlinear chaotic systems using a novel evolutionary computing strategy.KNOWLEDGE-BASED SYSTEMS,107,261-270.
MLA	Wang, Yudong,et al."Optimal targeting of nonlinear chaotic systems using a novel evolutionary computing strategy".KNOWLEDGE-BASED SYSTEMS 107(2016):261-270.