Integration of Optimal Experimental Design and Process Optimisation to An Enzyme Reaction System

被引：0

作者：

Yu, Hui ^{[1
]}

Guo, Jielong ^{[1
]}

Wei, Xian ^{[1
]}

Liang, Peidong ^{[2
]}

Zhao, Lijun ^{[3
]}

机构：

[1] Chinese Acad Sci, Fujian Inst Res Struct Matter, Quanzhou, Peoples R China

[2] Harbin Inst Technol, Fujian Quanzhou HIT Res Inst Engn & Technol, Quanzhou, Peoples R China

[3] Harbin Inst Technol, State Key Lab Robot & Syst, Harbin, Peoples R China

来源：

2019 CHINESE AUTOMATION CONGRESS (CAC2019) | 2019年

关键词：

optimal experimental design (OED); process optimisation; multi-objective design; parameter estimation; enzyme reaction system; MODEL-BASED DESIGN; IDENTIFICATION;

D O I：

10.1109/cac48633.2019.8997445

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A multi-objective experimental design strategy is proposed for a kinetically controlled synthesis process system by considering both the parameter estimation and the desired production yield. The input design is focused on maximising the desired production yield while the observation design is aimed at minimising the parameter estimation uncertainties. This multi-objective experimental design strategy is compared with the integrated experimental design method in which all design factors are optimised to improve parameter estimation quality. The optimal experimental design (OED) problem for observation design is relaxed to a semi-definite programming problem which is solved via interior-point method. Numerical studies demonstrate the efficiency of the proposed OED strategy as well as keeping high production yield. Parameter estimation uncertainties have been reduced significantly and they are near to those from integrated experimental design. The main point of this work is to introduce the idea of combining process optimisation with system identification so that the proposed model is closer to the real operation conditions in chemical processes.

引用

页码：3615 / 3620

页数：6

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