Modeling and Control of Dynamic Spatially Distributed Systems: Pharmaceutical Processes provides a balanced approach to help readers to get started quickly in the field of biochemical pharmaceuticals. From a theoretical perspective, dynamic spatially distributed systems are introduced to address their industrial applications. After identifying problems, the book provides readers with modeling and control system design techniques via a novel fuzzy set (class of objects with a continuum of grades of membership, to describe the grade of the object belonging to this fuzzy set) and intelligent computation methods. From an application perspective, the book provides a thorough understanding of Good Manufacture Practices (GMP) and the importance of identification, modelling, and intelligent control of such systems, reducing the test-and-error cost, and the R&D design time cycle of original drug development.
1. Chapter 4 Introduction to the depyrogenation tunnel - p. 101 2. Chapter 5 Conventional methods in modeling and simulation of depyrogenation tunnel - p. 129 3. Chapter 6 Quasi-Gaussian fuzzy sets and approximation - p. 149 4. Chapter 7 Type-2 quasi-Gaussian fuzzy systems - p. 177 5. Abstract - p. 177 6. 7.1 Universal approximation of fuzzy systems - p. 177 7. 7.2 Type-2 fuzzy systems - p. 178 8. 7.3 Hierarchical fuzzy systems (HFS) - p. 179 9. 7.4 Quasi-Gaussian fuzzy systems - p. 182 10. 7.5 State-space model based on QGFS - p. 195 11. 7.6 Summary - p. 198 12. References - p. 199 13. Part 3: Intelligent control methods of dynamic spatially distributed systems - p. 200 14. Chapter 8 General control methods of depyrogenation tunnel - p. 203 15. Chapter 9 Hierarchical fuzzy control of the depyrogenation tunnel - p. 247 16. Chapter 10 Conclusions and future prospects - p. 285 17. Index - p. 291
Modeling and Control of Dynamic Spatially Distributed Systems: Pharmaceutical Processes provides a balanced approach to help readers to get started quickly in the field of biochemical pharmaceuticals. From a theoretical perspective, dynamic spatially distributed systems are introduced to address their industrial applications. After identifying problems, the book provides readers with modeling and control system design techniques via a novel fuzzy set (class of objects with a continuum of grades of membership, to describe the grade of the object belonging to this fuzzy set) and intelligent computation methods. From an application perspective, the book provides a thorough understanding of Good Manufacture Practices (GMP) and the importance of identification, modelling, and intelligent control of such systems, reducing the test-and-error cost, and the R&D design time cycle of original drug development.
1. Chapter 4 Introduction to the depyrogenation tunnel - p. 101 2. Chapter 5 Conventional methods in modeling and simulation of depyrogenation tunnel - p. 129 3. Chapter 6 Quasi-Gaussian fuzzy sets and approximation - p. 149 4. Chapter 7 Type-2 quasi-Gaussian fuzzy systems - p. 177 5. Abstract - p. 177 6. 7.1 Universal approximation of fuzzy systems - p. 177 7. 7.2 Type-2 fuzzy systems - p. 178 8. 7.3 Hierarchical fuzzy systems (HFS) - p. 179 9. 7.4 Quasi-Gaussian fuzzy systems - p. 182 10. 7.5 State-space model based on QGFS - p. 195 11. 7.6 Summary - p. 198 12. References - p. 199 13. Part 3: Intelligent control methods of dynamic spatially distributed systems - p. 200 14. Chapter 8 General control methods of depyrogenation tunnel - p. 203 15. Chapter 9 Hierarchical fuzzy control of the depyrogenation tunnel - p. 247 16. Chapter 10 Conclusions and future prospects - p. 285 17. Index - p. 291
