摘要
在对工业过程进行建模时,模型规模庞大,现场运行工况点较多。构造全联立参数估计模型,模型规模随着工况数的增加成倍扩大,在初值较差的情况下,求解收敛性差。针对此问题,本文提出1种目标序贯式参数估计方法,按照特定规则分批调整目标,逐步添加约束,使得目标分批逼近设定值,最后在新的初值基础上求解联立参数估计优化命题。本文以PTA氧化反应工段模型为例,对其反应动力学常数进行参数估计,结果表明,目标序贯式参数估计收敛性强。
The modeling of a large-scale industrial process with multiple operating points is a complicate task,in which the parameter estimation plays an important role in determining a proper model.For a simultaneous mode parameter estimation,the model size increases with the number of operating points.In the case of a poor initial value,convergence of the large scale parameter estimation could be very poor.In this paper,a target-sequential parameter estimation method is proposed.It sequentially adjusts the target and adds the constraints to ensure the good convergence performance.Finally,the method is successfully applied to the PTA oxidation model.
出处
《计算机与应用化学》
CAS
CSCD
北大核心
2010年第1期46-50,共5页
Computers and Applied Chemistry
基金
国家高技术研究发展计划(863)资助项目(2007AA04Z192)
关键词
大规模
多工况
目标序贯式参数估计
large-scale, multiple operating points, target-sequential method, parameter estimation
