基于间歇反馈多维泰勒网的动力学模型

周博; 严洪森

doi:10.3724/SP.J.1004.2014.01517

基于间歇反馈多维泰勒网的动力学模型

doi: 10.3724/SP.J.1004.2014.01517

周博^1,2,
严洪森^1,2

1.
东南大学自动化学院南京 210096;
2.
东南大学复杂工程系统测量与控制教育部重点实验室南京 210096

基金项目:

国家自然科学基金（50875046，60934008）资助

详细信息

作者简介:
严洪森东南大学自动化学院教授. 主要研究方向为生产计划与调度，预测，知识化制造.E-mail：hsyan@seu.edu.cn

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- 文章访问数: 1864
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- 被引次数: 0
出版历程
- 收稿日期: 2013-08-19
- 修回日期: 2013-11-01
- 刊出日期: 2014-07-20

A Dynamics Model Based on Intermittent Feedback Multi-dimensional Taylor Network

ZHOU Bo^1,2,
YAN Hong-Sen^1,2

1.
School of Automation, Southeast University, Nanjing 210096;
2.
Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, Nanjing 210096

Funds:

Supported by National Natural Science Foundation of China (50875046, 60934008)

摘要

摘要: 具有羊群效应的系统，因为结构复杂，内部要素互相影响，参与其中的人类行为难以预测而不易建立整体模型. 本文提出建立间歇反馈多维泰勒网动力学模型方法，通过叠加的死区函数模拟了羊群效应中从众心理对系统产生的间歇反馈，结合多维泰勒网建立了适合普遍系统的一般动力学方程. 该方法区别于以往羊群效应的以个体研究为出发点，通过系统对外表征的数据波动建立了含有羊群效应的整体模型. 实例结果表明，这种基于间歇反馈多维泰勒网的动力学建模方法是可行和有效的.
- 间歇反馈 /
- 死区函数 /
- 多维泰勒网 /
- 动力学模型 /
- 系统辨识
Abstract: An integrated model of a dynamic system with herd behavior is difficult to be established because of its complex system structure, internal factors which influence each other, and involved human behaviors that are hard to predict. In this paper, a dynamics model based on intermittent feedback multi-dimensional Taylor network is proposed. According to the superposition of dead zone functions, the intermittent feedback caused by the crowd psychology of herd behavior is modeled, and the general dynamic equation suitable for common systems is established by combing the multi-dimensional Taylor network. The proposed method differs from the previous methods which start from individual studies of herd behavior, and establishes the integrated model containing herd behavior in terms of the data fluctuation which is externally characterized by the system. An example shows that the dynamics modeling method based on intermittent feedback multi-dimensional Taylor network is feasible and effective.
- Intermittent feedback /
- dead zone function /
- multi-dimensional Taylor network /
- dynamics model /
- system identifica-tion

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