On-line Estimation in Fed-batch Fermentation Process Using State Space Model and Unscented Kalman Filter

王建林; 赵利强; 于涛

doi:10.1016/S1004-9541(08)60351-1

Your Location：

Home >

Browse articles >

On-line Estimation in Fed-batch Fermentation Process Using State Space Model and Unscented Kalman Filter

Updated：2026-01-06

- On-line Estimation in Fed-batch Fermentation Process Using State Space Model and Unscented Kalman Filter
- Chinese Journal of Chemical Engineering Vol. 18, Issue 2, Pages: 258-264(2010)
- Affiliations：
  
  School of Information Science and Technology, Beijing University of Chemical Technology,Beijing,China,100029
- Author bio：
- Funds：
- DOI：10.1016/S1004-9541(08)60351-1
  CLC：
- Published：2010
- Accepted：
Scan QR Code
WANG Jianlin, ZHAO Liqiang, YU Tao. On-line Estimation in Fed-batch Fermentation Process Using State Space Model and Unscented Kalman Filter[J]. , 2010, 18(2): 258-264.
DOI：

WANG Jianlin, ZHAO Liqiang, YU Tao. On-line Estimation in Fed-batch Fermentation Process Using State Space Model and Unscented Kalman Filter[J]. , 2010, 18(2): 258-264. DOI： 10.1016/S1004-9541(08)60351-1.

摘要

Abstract

On-line estimation of unmeasurable biological variables is important in fermentation processes

directly influencing the optimal control performance of the fermentation system as well as the quality and yield of the targeted product.In this study

a novel strategy for state estimation of fed-batch fermentation process is proposed.By combining a simple and reliable mechanistic dynamic model with the sample-based regressive measurement model

a state space model is developed.An improved algorithm

swarm energy conservation particle swarm optimization(SECPSO)

is presented for the parameter identification in the mechanistic model

and the support vector machines(SVM) method is adopted to establish the nonlinear measurement model.The unscented Kalman filter(UKF) is designed for the state space model to reduce the disturbances of the noises in the fermentation process.The proposed on-line estimation method is demonstrated by the simulation experiments of a penicillin fed-batch fermentation process.

关键词

Keywords

references

Views

Downloads

CSCD

Alert me when the article has been cited

Submit

Tools

Publicity Resources

A fault diagnosis method for complex chemical process integrating shallow learning and deep learning

Stochastic neuro-swarming intelligence paradigm for the analysis of magneto-hydrodynamic Prandtl-Eyring fluid flow with diffusive magnetic layers effect over an elongated surface

Cascade refrigeration system synthesis based on hybrid simulated annealing and particle swarm optimization algorithm

Closed-loop scheduling optimization strategy based on particle swarm optimization with niche technology and soft sensor method of attributes-applied to gasoline blending process

Refrigeration system synthesis based on de-redundant model by particle swarm optimization algorithm

Related Author

Chunli Wang

Chengdong Gou

Wei Xu

Bing Sun

Zhe Yang

Yadong He

Muhammad Asif Zahoor Raja

Hira Ilyas

Related Institution

SINOPEC Research Institute of Safety Engineering Co., Ltd

State Key Laboratory of Chemical Safety

Future Technology Research Centre, National Yunlin University of Science and Technology, Yunlin

Department of Physical Sciences, University of Chenab, Gujrat

Department of Mathematics, University of Houston

⁰