Chaos control of a vibro-impact system with clearance based on RBF neural network

被引：0
|
作者：
Wei X.-J. [1 ]
Li N.-Z. [1 ]
Zhang H. [1 ]
Ding W.-C. [1 ]
机构：
[1] School of Mechatronic Engineering, Lanzhou Jiaotong University, Lanzhou
来源：
Zhendong Gongcheng Xuebao/Journal of Vibration Engineering | 2018年 / 31卷 / 02期
关键词：
Adaptive hybrid gravitational search algorithm; Chaos control; Nonlinear vibration; RBF neural network; Vibro-impact;
D O I：
10.16385/j.cnki.issn.1004-4523.2018.02.018
中图分类号：
学科分类号：
摘要：
By using intelligent optimization control method based on RBF neural network, the chaotic motion control of a vibro-impact system with clearance is studied in this paper. The chaos controller designed based on RBF neural network is used to output a small perturbation to adjust the controllable parameter of the vibro-impact system. Thus, the chaotic motion is controlled to the expected regular motion. At the same time, adaptive hybrid gravitational search algorithm (AHGSA) is combined with RBF neural network. By using the advantages of AHGSA algorithm with high convergence speed and global optimization ability, the parameters of chaos controller are optimized so that the blindness and subjectivity of the parameters selection of the chaos controller are avoided, and the performance of the chaos controller is improved. The proposed method in this paper does not need the exact mathematical model of the controlled system, so it is suitable for the cases where the exact mathematical model of the controlled system is unknown and only the experimental data can be obtained. © 2018, Nanjing Univ. of Aeronautics an Astronautics. All right reserved.
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页码：336 / 342
页数：6
相关论文
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