Research On The Soft-Sensing And Predictive Control Of Vinyl Acetate Polymerization Rate

The vinyl acetate(VAC) polymerization rate is an important quality parameters in the process of the Poly Vinyl Alcohol production, it has significant influence on security, economy of production process and product quality. At present, it mainly relies on manual sampling off-line detection and is controlled by the operators'experiences. This paper mainly studies two problems: on-line estimation of VAC polymerization rate by using soft-sensing technique and optimizing control of VAC polymerization rate by using the method of predictive control. The concrete research works are as follows:1. On the basis of comprehension of VAC polymerization process mechanics, various factors which affect VAC polymerization rate are analyzed and the soft-sensing model of VAC polymerization rate is established by using three methods including RBF neural network, Least Squares Support Vector Machine(LS-SVM) and Incremental Least Squares Support Vector Machines (ILS-SVM). Then the simulation based on the practical industrial data is researched and compared. The simulation results show that ILS-SVM can adjust training aims according to the error requirement and possesses high fitting and prediction precision, it has good abilities of generalization and the function of studying on line and is fit for on-line estimation of VAC polymerization rate.2. The process of VAC polymerization has the characteristics such as nonlinearity, time-varying, disturbance and time-delay, the traditional control strategy can't acquire satisfactory result, so the implicit generalized predictive control(GPC) algorithm is applied in the control of polymerization rate. This algorithm doesn't depend on exact model, and its ability of disturbance rejection and time-varying restraining has been enhanced greatly with the multi-step forecasting concept. So, the implicit GPC algorithm is adopted to design for the control system of VAC polymerization rate and simulation research is done with MATLAB. The simulation results show that the implicit GPC algorithm can obtain good control performance in both the dynamic response and tracking performance. Finally, the influence of main parameters of the implicit GPC algorithm is analyzed through simulation.Results shows that it is of importance to online prediction and optimizing control of VAC polymerization rate.