首页> 外文期刊>系统工程与电子技术(英文版) >Model algorithm control using neural networks for input delayed nonlinear control system
【24h】

Model algorithm control using neural networks for input delayed nonlinear control system

机译:输入延迟非线性控制系统的神经网络模型算法控制

获取原文
获取原文并翻译 | 示例
       

摘要

The performance of the model algorithm control method is partial y based on the accuracy of the system’s model. It is diffi-cult to obtain a good model of a nonlinear system, especial y when the nonlinearity is high. Neural networks have the ability to“learn”the characteristics of a system through nonlinear mapping to rep-resent nonlinear functions as wel as their inverse functions. This paper presents a model algorithm control method using neural net-works for nonlinear time delay systems. Two neural networks are used in the control scheme. One neural network is trained as the model of the nonlinear time delay system, and the other one pro-duces the control inputs. The neural networks are combined with the model algorithm control method to control the nonlinear time delay systems. Three examples are used to il ustrate the proposed control method. The simulation results show that the proposed control method has a good control performance for nonlinear time delay systems.
机译:基于系统模型的准确性,模型算法控制方法的性能为y。很难获得良好的非线性系统模型,尤其是在非线性度较高时。神经网络具有通过非线性映射“代表”非线性函数(如其反函数)来“学习”系统特性的能力。本文提出了一种基于神经网络的非线性时滞系统模型算法控制方法。控制方案中使用了两个神经网络。一个神经网络被训练为非线性时滞系统的模型,而另一个则产生控制输入。将神经网络与模型算法控制方法相结合,以控制非线性时滞系统。使用三个示例来说明所提出的控制方法。仿真结果表明,所提出的控制方法对非线性时滞系统具有良好的控制性能。

著录项

  • 来源
    《系统工程与电子技术(英文版)》 |2015年第1期|142-150|共9页
  • 作者

    Yuanliang Zhang; Kil To Chong;

  • 作者单位

    School of Mechanical Engineering, Huaihai Institute of Technology, Lianyungang 222005, China;

    School of Electronics and Information, Chonbuk National University, Jeonju 560756, South Korea;

  • 收录信息 中国科学引文数据库(CSCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号