The performance of an company depends both on its technological expertise and its managerial and organizational effectiveness. Production management is an important part of the process for manufacturing firms. The organization of production relies in general on the implementation of a certain number
Automatic Control of Bioprocesses (Control Systems, Robotics and Manufacturing)
β Scribed by Denis Dochain
- Publisher
- Wiley-ISTE
- Year
- 2008
- Tongue
- English
- Leaves
- 243
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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.
β¦ Table of Contents
Bioprocess Control......Page 4
Contents......Page 6
1.1. Introduction......Page 12
1.3. A schematic view of monitoring and control of a bioprocess......Page 13
1.4. Modeling and identication of bioprocesses: some key ideas......Page 14
1.5. Software sensors: tools for bioprocess monitoring......Page 15
1.7. Bioprocess monitoring: the central issue......Page 16
1.9. Bibliography......Page 17
2.1. Introduction......Page 18
2.2. Description of biochemical processes 2.2.1.......Page 19
2.3. Mass balance modeling 2.3.1.......Page 22
2.4. Mass balance models 2.4.1.......Page 25
2.5. Kinetics 2.5.1.......Page 31
2.6. Validation of the model 2.6.1.......Page 36
2.7. Properties of the models 2.7.1.......Page 40
2.8. Conclusion......Page 43
2.9. Bibliography......Page 44
3.1. Introduction......Page 48
3.2. Structural identi......Page 49
3.3. Practical identi......Page 53
3.4. Optimum experiment design for parameter estimation (OED/PE) 3.4.1.......Page 58
3.5. Estimation algorithms......Page 64
3.6. A case study: identi......Page 69
3.7. Bibliography......Page 76
4.1. Introduction......Page 80
4.2. Notions on system observability......Page 81
4.3. Observers for linear systems......Page 85
4.4. High gain observers 4.4.1.......Page 90
4.5. Observers for mass balance-based systems 4.5.1.......Page 95
4.6. Interval observers......Page 102
4.7. Conclusion......Page 111
4.8. Appendix: a comparison theorem......Page 112
4.9. Bibliography......Page 113
5.1. Introduction......Page 116
5.2. Parameter estimation based on the structure of the observer......Page 117
5.3. Recursive least squares estimator......Page 130
5.4. Adaptive state observer......Page 134
5.5. Conclusions......Page 141
5.6. Bibliography......Page 142
6.1. Introduction......Page 144
6.2. Bioprocess control: basic concepts 6.2.1.......Page 145
6.3. Stability of biological processes 6.3.1.......Page 148
6.4. Basic concepts of biological process control 6.4.1.......Page 151
6.4.2.......Page 152
6.4.3.......Page 153
6.5. Synthesis of biological process control laws......Page 154
6.6. Advanced control laws......Page 161
6.7. Specic approaches......Page 166
6.9. Bibliography......Page 171
7.1. Introduction......Page 174
7.2. Adaptive linearizing control of bioprocesses 7.2.1.......Page 175
7.2.2.......Page 177
7.2.3.......Page 184
7.3. Adaptive extremum-seeking control of bioprocesses......Page 189
7.3.1.......Page 190
7.3.2.......Page 192
7.3.3.......Page 198
7.4. Appendix: analysis of the parameter convergence......Page 203
7.5. Bibliography......Page 208
8.1. Introduction......Page 212
8.2. General de......Page 213
8.2.2.......Page 214
8.3. Fault detection and diagnosis......Page 215
8.3.1.......Page 216
8.3.2.......Page 219
8.3.3.......Page 223
8.4. Application to biological processes......Page 228
8.4.1.......Page 229
8.4.2.......Page 230
8.5. Conclusion......Page 232
8.6. Bibliography......Page 233
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