Journal Article10.1016/S1004-9541(08)60351-1
On-line Estimation in Fed-batch Fermentation Process Using State Space Model and Unscented Kalman Filter
Jianlin Wang,Liqiang Zhao,Tao Yu +2 more
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TL;DR: In this article, a 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, and an improved algorithm, swarm energy conservation particle swarm optimization (SECPSO), is presented for the parameter identification in the mechanistic model.
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About: This article is published in Chinese Journal of Chemical Engineering. The article was published on 01 Apr 2010. The article focuses on the topics: Extended Kalman filter & Kalman filter.
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Citations
Design of inferential sensors in the process industry: A review of Bayesian methods
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Development of a soft-sensor based on multi-wavelength fluorescence spectroscopy and a dynamic metabolic model for monitoring mammalian cell cultures.
TL;DR: It was demonstrated that the implementation of the EKF along with the dynamic model could improve the accuracy of the fluorescence‐based predictions at the sampling instances, and its major advantage was its capability to track the temporal evolution of key process variables between measurement instances obtained by the fluoresc‐based soft‐sensor.
41
Multi‐rate observer design and optimal control to maximize productivity of an industry‐scale fermentation process
Parth Piyushbhai Shah,M. Ziyan Sheriff,Mohammed Saad Faizan Bangi,Costas Kravaris,Joseph Sang-Il Kwon,Chiranjivi Botre,Junichi Hirota +6 more
TL;DR: In this paper , a multi-rate state observer for state estimation from plant measurements and a model predictive controller that maximizes the profitability of an industry-scale fermentation process (fermenter volume < 378,500 L) were designed.
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