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Advanced Instrumentation, Data Interpretation, and Control of Biotechnological Processes (Hardcover, 1998 ed.)
Loot Price: R4,366
Discovery Miles 43 660
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Advanced Instrumentation, Data Interpretation, and Control of Biotechnological Processes (Hardcover, 1998 ed.)
Expected to ship within 12 - 17 working days
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The scope of the field of biotechnological processes is very wide,
covering such processes as fermentations for production of
high-valued specialist chemicals (e.g. pharmaceuticals),
high-volume production of foods and feeds (e.g. yoghurt, cheese,
beer), as well as biological waste treatment, handling solid
(composting), liquid (activated sludge) and gaseous wastes
(biofilters). Compared to other engineering disciplines, the
introduction of modern optimization and control strategies is
lagging behind. Two main reasons can be identified. First, the
living organisms (or part thereof) that are central to these
processes make the mathematical modeling of the processes a
difficult task, and, since models are central to the development of
control systems, the on-line control problem is also complex. The
other difficulty stems from the absence, in most cases, of cheap
and reliable instrumentation suited to real-time monitoring. In
this book a number of advanced techniques is introduced to deal
with these problems. In the first part modern on-line hardware
sensors are discussed in detail (FIA, viable biomass measurement,
membrane inlet mass spectrometry, flow cytometry,
microcalorimetry). In the second part, novel model-based process
diagnosis and control techniques are dealt with, including advances
in bioprocess modeling and identification, data processing,
software sensor design, and on-line control algorithms. The book is
directed at engineers, researchers, and students in the field of
process control and systems theory as applied to industrial
biotechnological processes, as well as at bioengineers who have
some background in control engineering and wish to increase their
understanding ofhow advanced control theory applies to biological
processes.
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