Grade transition processes are critical for saving energy in polymerization

however

the traditional models do not pay much attention to the transitional process due to insufficiency of quality data. Therefore

based on the previous work of the three-stage decomposition modeling method

the overall process is further dealt with. In the polypropylene process

there are stable production processes for a single grade and grade transitional processes between two different grades. As these two kinds of processes have different dynamic characteristics

it is reasonable to divide data into different sub-domains according to different dynamic processes and develop sub-models in every domain. In this paper

construct ensemble of models based on different dynamic processes and a discriminant model to detect the beginning and completion of the transition were proposed. Finally

the proposed model was applied to industrial plant data and its higher prediction performance was verified

compared with a single model.