Mathematical Modeling and Control of Bioprocesses
Mathematical modeling is at the heart of most current developments in biological system analysis and bioprocess optimization and control. At the industrial scale, this evolution is reflected in process analytical technologies (PAT), digital twins, and Industry 4.0. This book focuses on various aspec...
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Format: | Electronic Book Chapter |
Language: | English |
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Basel
MDPI - Multidisciplinary Digital Publishing Institute
2023
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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100 | 1 | |a Bogaerts, Philippe |4 edt | |
700 | 1 | |a Vande Wouwer, Alain |4 edt | |
700 | 1 | |a Bogaerts, Philippe |4 oth | |
700 | 1 | |a Vande Wouwer, Alain |4 oth | |
245 | 1 | 0 | |a Mathematical Modeling and Control of Bioprocesses |
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300 | |a 1 electronic resource (302 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a Mathematical modeling is at the heart of most current developments in biological system analysis and bioprocess optimization and control. At the industrial scale, this evolution is reflected in process analytical technologies (PAT), digital twins, and Industry 4.0. This book focuses on various aspects of mathematical modeling at the microscopic and macroscopic scales, respectively, and demonstrates the potential of these methodologies to gain insight into the cell metabolism, to support the design of software sensors to reconstruct unmeasurable variables, or to establish model-based optimization of the operating conditions and/or feedback control of the bioprocesses. The range of applications is vast, including biopharmaceuticals, bioenergy, and the environment. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Technology: general issues |2 bicssc | |
650 | 7 | |a Chemical engineering |2 bicssc | |
653 | |a mathematical model | ||
653 | |a continuous bioreactor | ||
653 | |a biodegradation | ||
653 | |a phenol and p-cresol mixture | ||
653 | |a SKIP model | ||
653 | |a equilibrium points | ||
653 | |a stability analysis | ||
653 | |a global stabilizability | ||
653 | |a numerical simulation | ||
653 | |a MEC | ||
653 | |a hydrogen production | ||
653 | |a online optimization | ||
653 | |a golden section search | ||
653 | |a super-twisting controller | ||
653 | |a FPGA | ||
653 | |a bioplastic | ||
653 | |a copolymerization | ||
653 | |a polyhydroxyalkanoate | ||
653 | |a kinetic modeling | ||
653 | |a PID (PI) control | ||
653 | |a gain-scheduling | ||
653 | |a biotechnological cultivation process | ||
653 | |a dissolved oxygen concentration | ||
653 | |a flux variability analysis | ||
653 | |a flux balance analysis | ||
653 | |a sampling | ||
653 | |a metabolic network | ||
653 | |a elementary flux modes | ||
653 | |a set membership estimation | ||
653 | |a dynamic flux balance model | ||
653 | |a multiparametric programming | ||
653 | |a observability | ||
653 | |a variable structure system | ||
653 | |a process analytical technologies (PAT) | ||
653 | |a off-gas analytic | ||
653 | |a real-time monitoring | ||
653 | |a viable cell biomass | ||
653 | |a perfusion process | ||
653 | |a continuous process | ||
653 | |a single-use bioreactor (SUB) | ||
653 | |a oxygen uptake rate (OUR) | ||
653 | |a soft sensor | ||
653 | |a metabolic flux analysis | ||
653 | |a VERO cells | ||
653 | |a biotechnology | ||
653 | |a B. thuringiensis kurstaki | ||
653 | |a biopesticides | ||
653 | |a kinetic parameters | ||
653 | |a dynamic model | ||
653 | |a composting | ||
653 | |a optimization | ||
653 | |a mathematical modeling | ||
653 | |a anaerobic digestion | ||
653 | |a biogas | ||
653 | |a chemostat | ||
653 | |a maintenance | ||
653 | |a operating diagram | ||
653 | |a productivity | ||
653 | |a stability | ||
653 | |a optimal control | ||
653 | |a modelling | ||
653 | |a microalgae | ||
653 | |a nonlinear control | ||
653 | |a Pontryagin's principle | ||
653 | |a singular control | ||
653 | |a Droop model | ||
653 | |a photobioreactor | ||
653 | |a biomass | ||
653 | |a biorefinery design | ||
653 | |a process integration | ||
653 | |a scheduling | ||
653 | |a simulation | ||
653 | |a n/a | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/7209 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/100116 |7 0 |z DOAB: description of the publication |