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Full Description
Bioreactors: Animal Cell Culture Control for Bioprocess Engineering presents the design, fabrication, and control of a new type of bioreactor meant especially for animal cell line culture. The new bioreactor, called the "see-saw bioreactor," is ideal for the growth of cells with a sensitive membrane. The see-saw bioreactor derives its name from its principle of operation in which liquid columns in either limb of the reactor alternately go up and down. The working volume of the reactor is small, to within 15 L. However, it can easily be scaled up for large production in volume of cell mass in the drug and pharmaceutical industries.
The authors describe the principle of operation of the see-saw bioreactor and how to automatically control the bioprocess. They discuss different control strategies as well as the thorough experimental research they conducted on this prototype bioreactor in which they applied a time delay control for yield maximization.
To give you a complete understanding of the design and development of the see-saw bioreactor, the authors cover the mathematical model they use to describe the kinetics of fermentation, the genetic algorithms used for deriving the optimal time trajectories of the bioprocess variables, and the corresponding control inputs for maximizing the product yield. One chapter is devoted to the application of time delay control. Following a description of the bioreactor's working setup in the laboratory, the authors sum up their investigation and define the future scope of work in terms of design, control, and software sensors.
Contents
Introduction
A new type of bioreactor
Bioreactor modeling and control
Organization of the book
Novel see-saw bioreactor
Construction and working of the see-saw bioreactor
Theoretical modeling and simulation
Oxygen transfer to the falling film
Oxygen transfer to the flat surface
Total oxygen transfer in the bioreactor
Experiments to verify the modeling
Discussion of the results
Future scope of work
Simulation of bioprocess and development of BIPROSIM: A general purpose simulation program
Mathematical formulation of the bioprocess
Modes of operation
Adoption in the model parameters
The algorithm of BIPROSIM
Sample run
Dynamic optimization of a bioprocess using genetic algorithm
Historical background
Bioprocess model development
Application of genetic algorithm for control input optimization
Explanation of the application of GA
Algorithm 4.1
Flowchart of Algorithm 4.1
Subroutine "Child"
Subroutine "Mutate"
Algorithm 4.2
Flowchart of Algorithm 4.2
Results of the application of GA
Bioprocesses and time delay control
The problem of bioprocess control
Development of dynamic model
Time delay control
Time delay controller as bioprocess controller
Observer design
PID controllers for bioprocess control
Simulation results and discussions
Experimentation on the bioreactor
Instrumentation
Experimentation
Presentation of experimental results
Comparison between experimental and theoretical results
Summary
General conclusion and future scope of research
Overview of the work
General conclusion
Future scope of research
References
Appendix: Environmental control and sterilization of the bioreactor
