Abstract
One of the difficulties encountered in control and optimization of bioprocesses is the lack of reliable on-line sensors, which can measure the key processes' state variables. This chapter assesses the suitability of using RNNs for on-line biomass estimation in fed-batch fermentation processes. The proposed neural network sensor only requires the DO, feed rate and volume to be measured. The results show that RNNs are a powerful tool for implementing an on-line biomass softsensor in experimental fermentations.
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© 2006 Springer
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(2006). On-line Softsensor Development for Biomass Measurements using Dynamic Neural Networks. In: Modelling and Optimization of Biotechnological Processes. Studies in Computational Intelligence, vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32493-5_4
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DOI: https://doi.org/10.1007/978-3-540-32493-5_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30634-4
Online ISBN: 978-3-540-32493-5
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