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.