中国物理B ›› 2017, Vol. 26 ›› Issue (10): 100503-100503.doi: 10.1088/1674-1056/26/10/100503

• GENERAL • 上一篇    下一篇

A hybrid strategy to control uncertain nonlinear chaotic system

Yongbo Sui(隋永波), Yigang He(何怡刚), Wenxin Yu(于文新), Yan Li(李燕)   

  1. 1. The School of Electrical and Automation Engineering, Hefei University of Technology, Hefei 230009, China;
    2. School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411105, China;
    3. College of Electrical and Information Engineering, Hunan University, Changsha 430100, China
  • 收稿日期:2017-03-26 修回日期:2017-07-19 出版日期:2017-10-05 发布日期:2017-10-05
  • 通讯作者: Yigang He E-mail:18655136887@163.com
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant No. 51577046), the State Key Program of the National Natural Science Foundation of China (Grant No. 51637004), and the National Key Research and Development Plan "Important Scientific Instruments and Equipment Development" (Grant No. 2016YFF0102200).

A hybrid strategy to control uncertain nonlinear chaotic system

Yongbo Sui(隋永波)1, Yigang He(何怡刚)1, Wenxin Yu(于文新)2, Yan Li(李燕)3   

  1. 1. The School of Electrical and Automation Engineering, Hefei University of Technology, Hefei 230009, China;
    2. School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411105, China;
    3. College of Electrical and Information Engineering, Hunan University, Changsha 430100, China
  • Received:2017-03-26 Revised:2017-07-19 Online:2017-10-05 Published:2017-10-05
  • Contact: Yigang He E-mail:18655136887@163.com
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant No. 51577046), the State Key Program of the National Natural Science Foundation of China (Grant No. 51637004), and the National Key Research and Development Plan "Important Scientific Instruments and Equipment Development" (Grant No. 2016YFF0102200).

RichHTML

0

PDF (PC)

316

赞

摘要： In this paper, a new method, based on firefly algorithm (FA) and extreme learning machine (ELM), is proposed to control chaos in nonlinear system. ELM is an efficient predicted and classified tool, and can match and fit nonlinear systems efficiently. Hence, mathematical model of uncertain nonlinear system is obtained indirectly. For higher fitting accuracy, a novel swarm intelligence algorithm FA is drawn in our proposed way. The main advantage is that our proposed method can remove the limitation that mathematical model must be known clearly and can be applied to unknown nonlinear chaotic system.

关键词: chaos, firefly algorithm, extreme learning machine

Abstract: In this paper, a new method, based on firefly algorithm (FA) and extreme learning machine (ELM), is proposed to control chaos in nonlinear system. ELM is an efficient predicted and classified tool, and can match and fit nonlinear systems efficiently. Hence, mathematical model of uncertain nonlinear system is obtained indirectly. For higher fitting accuracy, a novel swarm intelligence algorithm FA is drawn in our proposed way. The main advantage is that our proposed method can remove the limitation that mathematical model must be known clearly and can be applied to unknown nonlinear chaotic system.

Key words: chaos, firefly algorithm, extreme learning machine

中图分类号:  (Nonlinear dynamics and chaos)

  • 05.45.-a
05.45.Gg (Control of chaos, applications of chaos)