Application of the Lyapunov Exponent to Evaluate Noise Filtering Methods for a Fed-batch Bioreactor for PHB Production

Bioautomation. 2008;9(1):1-14

 

Journal Homepage

Journal Title: Bioautomation

ISSN: 1313-261X (Print); 1312-451X (Online)

Publisher: Academic Publishing House

LCC Subject Category: Technology: Chemical technology: Biotechnology | Science: Biology (General)

Country of publisher: Bulgaria

Language of fulltext: English

Full-text formats available: PDF

 

AUTHORS


Pratap R. Patnaik

EDITORIAL INFORMATION

Peer review

Editorial Board

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Time From Submission to Publication: 20 weeks

 

Abstract | Full Text

Large-scale fed-batch fermentations are often subject to noise carried by the feed streams. This noise corrupts the process data and may destabilize the fermentation. So it is important to retrieve clear signals from noisy data. This is done by noise filters. The performances of some commonly used filters have been studied for poly-β-hydroxybutyrate production by Ralstonia eutropha. In simulated experiments, Gaussian noise was added to the flow rates of the carbon and nitrogen substrates. The filters were compared by means of the Lyapunov exponents of the outputs and their closeness to the noise-free performance. Negative exponents indicate a stable fermentation. An auto-associative neural filter performed the best, followed by a combination of a cusum filter and an extended Kalman filter. Butterworth filters were inferior and inadequate.