关键词:

结构逼近式混合神经网络, 间歇反应器, 建模, 串联混合神经网络

Abstract:

A new hybrid neural networks modeling approach, named structure approaching hybrid neural network (SAHNN) is presented in this paper.The characteristics and structure of this approach are introduced.The approach which combines first-principles model with neural networks fully utilizes structural information of known nonlinear system, makes neural networks a “grey-box”, describes and explains the consequence relation of system variables in a better way.A detailed analysis of SAHNN modeling was performed.Considering delayed measurement of outputs, simulation of a chemical batch reactor was performed and comparison of two types of hybrid neural network (HNN) was made.The results of simulation and comparison showed that the approach was a promising tool to model complicated nonlinear system effectively and could be utilized as a vehicle to control and optimize chemical reactors.

Key words:

结构逼近式混合神经网络, 间歇反应器, 建模, 串联混合神经网络