Research And Application On Grey-Box Modeling For Batch Reactor

Batch reactor plays an important role in the chemical industry. Batch reactor modeling is the prerequisite and basis of batch reactor design, optimization and process control. However, it is hard to accurately establish batch reactor model because of the factors, such as strong nonlinear behaviors, uncertainty, unknown disturbances and the limited online measurement information. In this paper, grey-box modeling approaches have been brought forward to solve the above-mentioned problems. And detailed processes of modeling of 3 grey-box methods were described in modeling batch reactor of producing accelerant for sulfuring rubber. The content is arranged as follows:Firstly, a modeling method, called Grey-box Modeling with Error Compensation (GMEC) had been put forward. The characteristics and structures of it are described in detailed in the paper. Idea of decomposition of system had been used to decompose the complicated system into the linear and non-linear part. Diagonal Recurrent Neural Network modeling (DRNN) was used to develop model of the linear part. Then, the output error between the actual system and the linear model was regarded as the training target of the non-linear model. The test result proves that GMEC is effective.Secondly, a modeling approach, named Grey-box Modeling Based on Fundamental Genes (GMFG) had been brought forward. Fundamental Genes had been introduced to describe the system behavior with insight information and prior-knowledge. A Structure Approaching Neural Network (SANN) was established, and Fundamental Genes (FGs) were regarded as the network nodes. Then, with Step-wise Regression Analysis (SRA), the Optimal FG (OFG) was selected to optimize the model structure and establish the relationship between system variables. The test result fully demonstrates that GMFG is effective.Thirdly, based on the GMFG, Improved Grey-box Modeling Based on Fundamental Genes (IGMFG) was developed to improve the deficiency in GMFG. It is mainly carried out two major improvements. The test result fully proves that IGMFG is effective.Finally, the summary and perspectives of the 3 grey-box modeling approaches are addressed.