Human-simulated intelligent control based on parameters correcting by fuzzy neural network

ZHANG Guan-yu; TIAN Jian-yan; ZHANG Wei-jie; QIU Hua-dong; ZHANG Chan-ai

doi:10.13873/j.1000-97872013.10.005

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Human-simulated intelligent control based on parameters correcting by fuzzy neural network

更新时间：2025-09-11

- Human-simulated intelligent control based on parameters correcting by fuzzy neural network
- Vol. 32, Issue 10, Pages: 30-33(2013)
- 作者机构：
  
  1. 太原理工大学
  2. 新型传感器与智能控制教育部重点实验室
  3. 太原钢铁集团有限公司热连轧厂
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872013.10.005
  CLC： TP183;TG334.9
- Published：2013
- 稿件说明：
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[1]张贯宇,田建艳,张维杰,邱华东,张婵爱.基于模糊神经网络参数整定的仿人智能控制[J].传感器与微系统,2013,32(10):30-33.

ZHANG Guan-yu, TIAN Jian-yan, ZHANG Wei-jie, et al. Human-simulated intelligent control based on parameters correcting by fuzzy neural network[J]. 2013, 32(10): 30-33.
[1]张贯宇,田建艳,张维杰,邱华东,张婵爱.基于模糊神经网络参数整定的仿人智能控制[J].传感器与微系统,2013,32(10):30-33. DOI： 10.13873/j.1000-97872013.10.005.

ZHANG Guan-yu, TIAN Jian-yan, ZHANG Wei-jie, et al. Human-simulated intelligent control based on parameters correcting by fuzzy neural network[J]. 2013, 32(10): 30-33. DOI： 10.13873/j.1000-97872013.10.005.

摘要

针对目前带钢厚度控制精度低

不能满足生产要求的问题

将模糊神经网络与仿人智能控制有机结合

设计了一种基于模糊神经网络参数整定的热轧带钢厚度仿人智能控制策略

利用模糊神经网络对仿人智能控制器的参数进行了整定。Matlab仿真结果表明:基于模糊神经网络参数整定的仿人智能控制优于PID控制

为解决复杂工业过程的控制提供了一种新的、有效的方法。

Abstract

Aiming at problem of low control precision and cannot meet requirement of production of strip thickness

combines fuzzy neural network with human-simulated intelligent control technology

design humansimulated intelligent control strategy of hot rolled strip steel thickness based on fuzzy neural network parameters setting

correct human-simulated intelligent controller parameters using fuzzy neural network.The simulation experiment result by Matlab shows that the human-simulated intelligent control method which based on fuzzy neural network has a better performance compared with PID control

it can provide a new effective method for the control of complex industrial process.

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references

复杂过程的多模态仿人智能控制策略 [J]. 王静,肖超. 微电子学 . 2013(02)

BP神经网络学习率的优化方法 [J]. 高红. 长春师范学院学报(自然科学版) . 2010(04)

复杂工业过程的预测控制理论及其应用 [J]. 赵均,徐祖华,钱积新. 自动化与信息工程 . 2009(03)

一种仿人智能控制参数整定方法 [J]. 刘军,胡章军. 控制工程 . 2006(S1)

带钢热连轧AGC系统实时仿真 [J]. 王正林,孙一康,彭开香. 北京科技大学学报 . 2006(02)

仿人智能控制器的动态特性参数整定方法 [J]. 杨飚,张曾科. 信息与控制 . 2004(06)

热连轧带钢厚度智能控制系统研究 [D]. 王宜斌. 西安建筑科技大学 2008

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