MWD MODELING AND CONTROL FOR POLYMERIZATION via B-SPLINE NEURAL NETWORK
This paper firstly introduces the structure and characteristics of B-spline-based neural network,and then presents a new approach to modeling and control of molecular mass distribution for polymerization. Utilizing the nonlinear mapping of B-spline functions and iterative minimum least square algorithm,the model of MWD in polymerization process has been built. Based on the MWD estimated by the neural network model and optimal performance index,the control sequences are synthesized in order to make MWD close to the target distribution. Taking a pilot scale rig,in which bulk polymerization of styrene takes place,as a simulated object,the modeling and control procedures are studied and implemented,and the feasibility of the approach is established.