关键词: 聚合物分子量分布, 正交多项式组合神经网络, 矩, 输出反馈, 非线性多变量系统

Abstract: The combined orthogonal polynomial neural network has been used to model the molecular weight distribution(MWD)of polymers,therefore MWD is decomposed into a function of its moments.In this paper,tracking of a desired MWD is realized through choosing moment vector as directive control goal.In order to obtain the control solution for the non-affine nonlinear multivariate system,a model architecture utilizing an improved nonlinear autoregressive orthogonal polynomial neural network is proposed,and the linear relationship between the model outputs and current control strategy U(k)is realized.Taking the higher-dimensional controlled variable into consideration,the paper shows the equivalent of independent variables in moment vector and parameters of distribution function,thus the criterion of moment vector dimensionality reduction are proposed to transforming the higher-dimensional output control problem into low-dimensional.Based on the improved neural network model,the output feedback control method is used for the moment control of MWD,and then the tracking of desired MWD is realized.The control method is tested on styrene polymerization reacted in CSTR,and simulation results proved the effectiveness of the method.This paper proposed a new solution for modeling and control of nonlinear multivariate system.

Key words: molecular weight distribution of polymer, combined orthogonal polynomial neural networks, moments, output feedback method, nonlinear multivariate system