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Journal of Zhejiang University SCIENCE B 2005 Vol.6 No.6 P.530~534


On-line estimation of concentration parameters in fermentation processes

Author(s):  XIONG Zhi-hua, HUANG Guo-hong, SHAO Hui-he

Affiliation(s):  Institute of Automation, Shanghai Jiaotong University, Shanghai 200030, China

Corresponding email(s):   zhxiong@sjtu.edu.cn

Key Words:  Gaussian processes (GP), Expectation maximization (EM), Multiple models, Soft sensor, Yeast concentration, Fermentation processes

XIONG Zhi-hua, HUANG Guo-hong, SHAO Hui-he. On-line estimation of concentration parameters in fermentation processes[J]. Journal of Zhejiang University Science B, 2005, 6(6): 530~534.

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%T On-line estimation of concentration parameters in fermentation processes
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T1 - On-line estimation of concentration parameters in fermentation processes
A1 - XIONG Zhi-hua
A1 - HUANG Guo-hong
A1 - SHAO Hui-he
J0 - Journal of Zhejiang University Science B
VL - 6
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SP - 530
EP - 534
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2005.B0530

It has long been thought that bioprocess, with their inherent measurement difficulties and complex dynamics, posed almost insurmountable problems to engineers. A novel software sensor is proposed to make more effective use of those measurements that are already available, which enable improvement in fermentation process control. The proposed method is based on mixtures of gaussian processes (GP) with expectation maximization (EM) algorithm employed for parameter estimation of mixture of models. The mixture model can alleviate computational complexity of GP and also accord with changes of operating condition in fermentation processes, i.e., it would certainly be able to examine what types of process-knowledge would be most relevant for local models’ specific operating points of the process and then combine them into a global one. Demonstrated by on-line estimate of yeast concentration in fermentation industry as an example, it is shown that soft sensor based state estimation is a powerful technique for both enhancing automatic control performance of biological systems and implementing on-line monitoring and optimization.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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