Process Control Design for Industrial Applications

Table of contents

1. Cover
2. Title
3. Copyright
4. Preface
5. List of Acronyms and Notations
6. 1 Introduction – Models and Dynamic Systems
   1. 1.1. Overview
   2. 1.2. Industrial process modeling
   3. 1.3. Model classes
7. 2 Linear Identification of Closed-Loop Systems
   1. 2.1. Overview of system identification
   2. 2.2. Framework
   3. 2.3. Preliminary identification of a CL process
   4. 2.4. CLOE class of identification methods
   5. 2.5. Application: identification of active suspension
8. 3 Digital Control Design Using Pole Placement
   1. 3.1. Digital proportional-integral-derivative algorithm control
   2. 3.2. Digital polynomial RST control
   3. 3.3. RST control by pole placement
   4. 3.4. Predictive RST control
9. 4 Adaptive Control and Robust Control
   1. 4.1. Adaptive polynomial control systems
   2. 4.2. Robust polynomial control systems
10. 5 Multimodel Control
    1. 5.1. Construction of multimodels
    2. 5.2. Stabilization and control of multimodels
    3. 5.3. Design of multimodel command: fuzzy approach
    4. 5.4. Trajectory tracking
11. 6 Ill-Defined and/or Uncertain Systems
    1. 6.1. Study of the stability of nonlinear systems from vector norms
    2. 6.2. Adaptation of control
    3. 6.3. Overvaluation of the maximum error for various applications
    4. 6.4. Fuzzy secondary loop control
12. 7 Modeling and Control of an Elementary Industrial Process
    1. 7.1. Modeling and control of fluid transfer processes
    2. 7.2. Modeling and controlling liquid storage processes
    3. 7.3. Modeling and controlling the storage process of a pneumatic capacitor
    4. 7.4. Modeling and controlling heat transfer processes
    5. 7.5. Modeling and control of component transfer processes
13. 8 Industrial Applications – Case Studies
    1. 8.1. Digital control for an installation of air heating in a steel plant
    2. 8.2. Control and optimization of an ethylene installation
    3. 8.3. Digital control of a thermoenergy plant
    4. 8.4. Extremal control of a photovoltaic installation
14. Appendix A: Matrix Transformation from Any Representation to the Companion Form or Arrow Form
    1. A1.1. Transition from a companion matrix to an arrow form matrix
    2. A1.2. Direct transition of a matrix of any form to an arrow form
15. Appendix B: Determination of the Maximum Error for Pole Placement for a Nonlinear Third-Order Process
16. Appendix C: Determining the Attractor in a Nonlinear Process Controlled by Linear Decoupling
17. Appendix D: Overvaluation of the Maximum Error in a Tracking Problem for a Lur’e Postnikov Type Process
18. Blibliography
19. Index
20. End User License Agreement