This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
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 of how advanced control theory applies to biological processes.
