基于DRNN神经网络的造纸过程定量水分解耦控制分析
Analysis of Quantitative Water Decomposition Coupling Control in Papermaking Process Based on DRNN
郑敏1
作者信息
摘要
阐述造纸过程定量水分的控制技术,利用Matlab建立定量水分数学模型,分别采用常规PID算法和DRNN神经网络算法对定量水分耦合模型进行解耦控制,探讨神经网络来整定PID控制器参数,不依赖控制对象的数学模型就可以实现解耦控制.仿真结果表明,DRNN神经网络算法响应速度更快,自适应能力显著增强,可进一步改善系统的动态性能.
Abstract
This paper expounds the control technology of quantitative moisture in the papermaking process,establishes a mathematical model of quantitative moisture content using Matlab,decouples the quantitative moisture coupling model using conventional PID algorithm and DRNN neural network algorithm,and explores the use of neural networks to adjust PID controller parameters.Decoupling control can be achieved without relying on the mathematical model of the control object.The simulation results show that the DRNN neural network algorithm has a faster response speed and significantly enhanced adaptive ability,which can further improve the dynamic performance of the system.
关键词
智能控制/定量水分数学模型/DRNN神经网络算法Key words
intelligent control/quantitative moisture mathematical model/DRNN neural network algorithm引用本文复制引用
基金项目
2021年廊坊市科学技术研究与发展计划自筹经费项目(2021011031)
出版年
2024
NETL
NSTL
维普
万方数据