针对大型聚乙烯工业装置质量指标实时估计和牌号切换的复杂性,基于乙烯聚合原理推导了大型聚乙烯工业装置质量指标实时预测模型,利用模块反推方法推导了参数更新律,提出了一种渐近跟踪状态观测器设计方法用于根据实验室分析数据反馈修正质量指标并实时估计模型参数。参数更新律设计采用新型神经动力学方法实时求解,通过引入切换修正保证了参数更新律的鲁棒性,选取足够大的增益矩阵可使观测器渐近跟踪系统状态。所提方法在大型聚乙烯工业装置上的应用结果证实了其有效性和可行性,为实现大型聚乙烯工业装置先进控制奠定了基础。
A predictive model of resin quality is deduced for industrial polyethylene process based on the kinetics of ethylene polymerization.According to the off-line lab analytical data,a parameter update law is deduced based on the predictive model of resin quality and an asymptotic tracking state observer design method is proposed to update the estimation of resin quality and model parameter.With the new method for solving the neural dynamics,the adaplive parameter update law is deduced,to ensure the robustness of parameter update law,and a sufficiently large observer gain matrix is selected to asymptotically track the system state.The application results with the proposed method to an industrial Unipol licensed linear low-density polyethylene process show the feasibility and effectiveness of the proposed.