集气管压力系统的神经网络逆解耦复合控制  

Neural Network Inverse Decoupling Compound Control of the Gas Collector Pressure System

作　　者：田晴[1] 曹秀爽[2] 

机构地区：[1]河北联合大学电气工程学院,河北唐山063009 [2]唐山学院信息工程系,河北唐山063009

出　　处：《河北联合大学学报（自然科学版）》2015年第1期95-99,共5页Journal of Hebei Polytechnic University:Social Science Edition

基　　金：唐山市科学技术研究与发展计划项目;项目编号:11110211a

摘　　要：针对集气管压力系统具有强干扰、强耦合、非线性、多参数等特性,依据逆系统解耦原理,分析了集气管压力系统数学模型的可逆性;采用对非线性具有较强逼近能力的BP神经网络,逼近集气管压力系统的逆系统;神经网络逆系统与原系统构成伪线性解耦复合系统,实现集气管压力系统的神经网络逆解耦复合控制。仿真结果表明该方法实现了系统解耦,具有一定的应用性。For collectors＇pressure system strong interference,coupled,nonlinear,multi-parameter and oth-er characteristics,based on the inverse system decoupling principle,the reversibility of the mathematical model of the gas collectors＇pressure system is analyzed.BP neural network which has strong nonlinear ap-proximation ability is applied,to approximate inverse system of gas collectors＇pressure system.Neural net-work inverse system with the original system composes of the pseudo linear decoupling composite system. The neural network inverse decoupling control of gas collectors＆#39;pressure system is implemented.The simu-lation results show that this method realizes decoupling,has a certain application.

关 键 词：集气管压力 神经网络 逆系统 解耦控制 

分 类 号：TQ520.5[化学工程—煤化学工程]