基于动态模糊神经网络逆系统的焦炉集气管压力解耦控制  

Decoupling control of coke oven gas collector pressure based on inverse system using the dynamic neural-fuzzy network

作　　者：刘昕明[1] 吕亮 罗伟 Liu Xinming;Lyu Liang;Luo Wei(College of Electrical and Control Engineering,Liaoning Technical University,Huludao 125105,China;Nanchang Urban Planning and Design Research Institute,Nanchang 330000,China)

机构地区：[1]辽宁工程技术大学电气与控制工程学院,辽宁葫芦岛125105 [2]南昌市城市规划设计研究总院,江西南昌330000

出　　处：《无线互联科技》2019年第21期158-159,共2页Wireless Internet Technology

基　　金：辽宁省教育厅科学研究一般项目;项目编号：LJYL013

摘　　要：焦炉集气管压力系统具有多变量、强耦合、非线性和纯滞后等特点,难以建立准确的数学模型。文章采用基于动态模糊神经网络的逆系统方法对集气管压力系统进行解耦,建立逆系统解耦器,并且设计了集气管压力单神经元PID控制器。该方法有效地实现了多焦炉集气管压力解耦控制,能较好地满足多焦炉集气管压力控制的工艺要求。The coke oven gas collector pressure system has the characteristics of multi-variable, strong coupling, nonlinearity and pure hysteresis. The inverse system method based on fuzzy neural network is used to decouple the pressure system of gas collector, an inverse system decouple is established, and a single neuron PID controller is designed in this paper. This method effectively realizes the decoupling control of coke oven gas collector pressure, and can better meet the technical requirements of multi coke oven gas collector pressure control.

关 键 词：焦炉集气管压力 动态模糊神经网络 解耦控制 

分 类 号：TQ5[化学工程]