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Informationen zum Autor Denis Dochain is a Professor at the CESAME (Centre for Systems Engineering and Applied Mechanics) of the Université Catholique de Louvain and Honorary Research Director of the FNRS (Fonds National de la Recherche Scientifique, National Fund for Scientific Research), France. He is associate editor of Automatica, the IEEE Transactions on Automatic Control and the Journal of Process Control. Klappentext Giving an overview of the challenges in the control of bioprocesses, this comprehensive book presents key results in various fields, including: dynamic modeling; dynamic properties of bioprocess models; software sensors designed for the on-line estimation of parameters and state variables; control and supervision of bioprocesses. Zusammenfassung Giving an overview of the challenges in the control of bioprocesses! this comprehensive book presents key results in various fields! including: dynamic modeling; dynamic properties of bioprocess models; software sensors designed for the on-line estimation of parameters and state variables; control and supervision of bioprocesses. Inhaltsverzeichnis Chapter 1. What are the Challenges for the Control of Bioprocesses? 11 Denis DOCHAIN 1.1. Introduction . 11 1.2. Specific problems of bioprocess control 12 1.3. A schematic view of monitoring and control of a bioprocess 12 1.4. Modeling and identification of bioprocesses: some key ideas 13 1.5. Software sensors: tools for bioprocess monitoring 14 1.6. Bioprocess control: basic concepts and advanced control15 1.7. Bioprocess monitoring: the central issue 15 1.8. Conclusions 16 1.9. Bibliography 16 Chapter 2. Dynamic Models of Biochemical Processes: Properties of Models 17 Olivier BERNARD and Isabelle QUEINNEC 2.1. Introduction 17 2.2. Description of biochemical processes 18 2.2.1. Micro-organisms and their use 18 2.2.2. Types of bioreactors 19 2.2.3. Three operating modes 19 2.3. Mass balance modeling 21 2.3.1. Introduction 21 2.3.2. Reaction scheme 21 2.3.3. Choice of reactions and variables 23 2.3.4. Example 1 23 2.4. Mass balance models 24 2.4.1. Introduction 24 2.4.2. Example 2 24 2.4.3. Example 3 25 2.4.4. Matrix representation 25 2.4.4.1. Example 2 (continuation) 26 2.4.4.2. Example 1 (continuation) 26 2.4.5. Gaseous flow 27 2.4.6. Electroneutrality and affinity constants 27 2.4.7. Example 1 (continuation) 28 2.4.8. Conclusion 29 2.5. Kinetics 30 2.5.1. Introduction 30 2.5.2. Mathematical constraints 30 2.5.2.1. Positivity of variables 30 2.5.2.2. Variables necessary for the reaction 31 2.5.2.3. Example 1 (continuation) 31 2.5.2.4. Phenomenological knowledge 31 2.5.3. Specific growth rate 32 2.5.4. Representation of kinetics by means of a neural network 34 2.6. Validation of the model 35 2.6.1. Introduction 35 2.6.2. Validation of the reaction scheme 35 2.6.2.1. Mathematical principle 35 2.6.2.2. Example 4 36 2.6.3. Qualitative validation of model 37 2.6.4. Global validation of the model 39 2.7. Properties of the models 39 2.7.1. Boundedness and positivity of variables 39 2.7.2. Equilibrium points and local behavior 40 2.7.2.1. Introduction 40 2.8. Conclusion 42 2.9. Bibliography 43 Chapter 3. Identification of Bioprocess Models 47 Denis DOCHAIN and Peter VANROLLEGHEM 3.1. Introduction 47 3.2. Structural identifiability 48 3.2.1. Development in Taylor series 49 3.2.2. Generating series 50 3.2.3. Examples for the application of the methods of development in series 50 3.2.4. Some observations o...
