Estimation of reaction kinetic parameters based on modified stochastic gradient descent

被引：0
|
作者：
Tang L.-S. [1 ]
Chen W.-F. [1 ]
机构：
[1] School of Information Engineering, Zhejiang University of Technology, Hangzhou
来源：
Gao Xiao Hua Xue Gong Cheng Xue Bao/Journal of Chemical Engineering of Chinese Universities | 2022年 / 36卷 / 03期
关键词：
Extended objective; Parameter estimation; Sensitivity matrix; Stochastic optimization;
D O I：
10.3969/j.issn.1003-9015.2022.03.015
中图分类号：
学科分类号：
摘要：
Considering the solution difficulty of conventional optimization algorithm in parameter estimation using all sampled data, a reaction kinetic parameter estimation method based on modified stochastic gradient descent was proposed by introducing stochastic optimization and extended objective function in the framework of simultaneous solution. Firstly, the mechanism of large-scale system with multiple data sets was modeled, and the sensitivity matrix was obtained based on the sensitivity differential equation method, and the model scaling technique was used to deal with the simultaneous convergence problem of multi-state variables to multi-parameter estimation. In order to reduce the influence of noise variance in the iterative process, based on the existing stochastic average gradient descent method, the stochastic extended objective function was applied to increase the amount of information for calculating the gradient in the objective function, and the theoretical convergence of the method was given. Relevant numerical simulation results have verified the effectiveness and feasibility of the proposed method. © 2022, Editorial Board of "Journal of Chemical Engineering of Chinese Universities". All right reserved.
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页码：426 / 436
页数：10
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