一类微生物连续发酵过程的GMA系统及其参数辨识

兰州理工大学学报 ›› 2024, Vol. 50 ›› Issue (4): 153-158.

一类微生物连续发酵过程的GMA系统及其参数辨识

赵雅芝, 徐恭贤^*

渤海大学数学科学学院, 辽宁锦州 121013

收稿日期:2022-12-08 出版日期:2024-08-28 发布日期:2024-08-30
通讯作者: 徐恭贤(1976-),男,辽宁庄河人,博士,教授.Email:gxxu@bhu.edu.cn
基金资助:
国家自然科学基金(11101051,62273056),辽宁省自然科学基金(2022-MS-371),辽宁省教育厅科学研究项目(JYTMS20231628)

GMA system and parameter identification for a class of microbial continuous fermentation process

ZHAO Ya-zhi, XU Gong-xian

School of Mathematical Sciences, Bohai University, Jinzhou 121013, China

Received:2022-12-08 Online:2024-08-28 Published:2024-08-30

摘要/Abstract

摘要： 研究了一类微生物连续发酵过程的数学建模与参数辨识问题. 提出了微生物连续发酵过程的GMA系统数学模型,并论述了该系统的数学性质. 以状态变量的稳态实验数据与计算数据的误差平方和最小为性能指标构建了参数辨识模型. 基于等价对数变换和SQP算法提出了一种参数辨识模型的求解方法,通过计算获得了最优参数值. 与已有文献误差结果相比,取得了更小的浓度误差值.

关键词: 连续发酵, GMA系统, 1,3-丙二醇, 参数辨识

Abstract: The mathematical modeling and parameter identification of a class of microbial continuous fermentation processes are studied here. The mathematical model of the GMA system for the continuous microbial fermentation process is proposed, and its mathematical properties of the system are also presented. The parameter identification model is constructed by minimizing the squared error sum between the experimental steady-state data and calculated values of state variables. Based on the equivalent logarithmic transformation and SQP algorithm, a solution method for the parameter identification model is proposed. The optimal parameter values are obtained through the calculation. Compared with the existing error results in the literature, this approach achieves smaller concentration error value.

Key words: continuous fermentation, GMA system, 1,3-propanediol, parameter identification

中图分类号:

赵雅芝, 徐恭贤. 一类微生物连续发酵过程的GMA系统及其参数辨识[J]. 兰州理工大学学报, 2024, 50(4): 153-158.

ZHAO Ya-zhi, XU Gong-xian. GMA system and parameter identification for a class of microbial continuous fermentation process[J]. Journal of Lanzhou University of Technology, 2024, 50(4): 153-158.

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