Fuzzy estimation of a yeast fermentation parameters
Joint Authors
al-Taibi, Mahmud
Vincent, Nicole
Charef, Chabbi
Source
The International Arab Journal of Information Technology
Issue
Vol. 2, Issue 2 (30 Apr. 2005), pp.97-103, 7 p.
Publisher
Publication Date
2005-04-30
Country of Publication
Jordan
No. of Pages
7
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
The dynamics of fermentation processes are very complex and not completely known.
Some state variables are non-measurable, and the process parameters are strongly time dependent.
Recently, there are some control methods like fuzzy learning and neural networks, which are promising in dealing with non-linearity, complexity, and uncertainly of these processes.
These methods are suitable for the modeling of these systems, which are difficult to describe mathematically.
The fuzzy learning methods are useful for the modeling, they are less demanding on the mathematical model and a priori knowledge about the processes.
Different techniques for estimating the state variables (that are non-measurable) in the fermentation process have been investigated.
A non-linear auto-regressive with exogenous input (NARX) model was developed using process data from a pilot bioreactor.
The fermentation process is splitted into three phases, where each phase was treated separately.
Generally, fuzzy models have a capability of dividing an input space into several subspaces (fuzzy clustering), where each subspace is supposed to give a local linear model.
In our work, we used global learning where the local models are less interpretable, but the global model accuracy is satisfying, and the fuzzy partition matrix is obtained by applying the Gustafson-Kessel algorithm.
The fermentation parameters are estimated for a batch and a fed-batch culture.
The number of inputs to our fuzzy model are three for a first simulation.
We used four inputs for a second simulation, in order to detect some correlations among inputs.
The results show that estimated parameters are close to the measured (or calculated) ones.
The parameters used in the computation are identified using batch experiments.
American Psychological Association (APA)
al-Taibi, Mahmud& Charef, Chabbi& Vincent, Nicole. 2005. Fuzzy estimation of a yeast fermentation parameters. The International Arab Journal of Information Technology،Vol. 2, no. 2, pp.97-103.
https://search.emarefa.net/detail/BIM-12111
Modern Language Association (MLA)
al-Taibi, Mahmud…[et al.]. Fuzzy estimation of a yeast fermentation parameters. The International Arab Journal of Information Technology Vol. 2, no. 2 (Apr. 2005), pp.97-103.
https://search.emarefa.net/detail/BIM-12111
American Medical Association (AMA)
al-Taibi, Mahmud& Charef, Chabbi& Vincent, Nicole. Fuzzy estimation of a yeast fermentation parameters. The International Arab Journal of Information Technology. 2005. Vol. 2, no. 2, pp.97-103.
https://search.emarefa.net/detail/BIM-12111
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p.102-103
Record ID
BIM-12111