Aiming at the time-variant and nonlinear characteristics of polypropylene production process

a discount moving window recursive PLS based on data blocks (DMW-RPLS) is proposed in the paper. Based on PLS

the amount of data blocks is controlled through bringing in the moving window and data blocks are discounted through bringing in the forgetting factor

and then updates the soft model in order to predict the measuring variables in real time.Through the study for the polypropylene melt index

the result shows the discount moving window recursive PLS can reduce the calculation and overcome the data saturation

and then use the process information effectively to reflect the process characteristic quickly and accurately.