Next Article in Journal
Energy Saving and Low-Cost-Oriented Design Processes of Blank’s Dimensions Based on Multi-Objective Optimization Model
Previous Article in Journal
Essential and Recovery Oils from Matricaria chamomilla Flowers as Environmentally Friendly Fungicides Against Four Fungi Isolated from Cultural Heritage Objects
Open AccessArticle

Adaptive Control of Biomass Specific Growth Rate in Fed-Batch Biotechnological Processes. A Comparative Study

Department of Automation, Kaunas University of Technology, LT-51367 Kaunas, Lithuania
*
Author to whom correspondence should be addressed.
Processes 2019, 7(11), 810; https://doi.org/10.3390/pr7110810
Received: 16 October 2019 / Revised: 29 October 2019 / Accepted: 1 November 2019 / Published: 4 November 2019
(This article belongs to the Special Issue Application of Systems Engineering Principles to Bioprocessing )
This article presents a comparative study on the development and application of two distinct adaptive control algorithms for biomass specific growth rate control in fed-batch biotechnological processes. A typical fed-batch process using Escherichia coli for recombinant protein production was selected for this research. Numerical simulation results show that both developed controllers, an adaptive PI controller based on the gain scheduling technique and a model-free adaptive controller based on the artificial neural network, delivered a comparable control performance and are suitable for application when using the substrate limitation approach and substrate feeding rate manipulation. The controller performance was tested within the realistic ranges of the feedback signal sampling intervals and measurement noise intensities. Considering the efforts for controller design and tuning, including development of the adaptation/learning algorithms, the model-free adaptive control algorithm proves to be more attractive for industrial applications, especially when only limited knowledge of the process and its mathematical model is available. The investigated model-free adaptive controller also tended to deliver better control quality under low specific growth rate conditions that prevail during the recombinant protein production phase. In the investigated simulation runs, the average tracking error did not exceed 0.01 (1/h). The temporary overshoots caused by the maximal disturbances stayed within the range of 0.025–0.11 (1/h). Application of the algorithm can be further extended to specific growth rate control in other bacterial and mammalian cell cultivations that run under substrate limitation conditions. View Full-Text
Keywords: adaptive control; biotechnological processes; fed-batch process; gain scheduling technique; model-free adaptive control; specific growth rate control adaptive control; biotechnological processes; fed-batch process; gain scheduling technique; model-free adaptive control; specific growth rate control
Show Figures

Figure 1

MDPI and ACS Style

Galvanauskas, V.; Simutis, R.; Vaitkus, V. Adaptive Control of Biomass Specific Growth Rate in Fed-Batch Biotechnological Processes. A Comparative Study. Processes 2019, 7, 810.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop