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Process Control Design for Industrial Applications

Book Description

This book presents the most important methods used for the design of digital controls implemented in industrial applications. The best modelling  and identification techniques for dynamical systems are presented as well as the algorithms for the implementation of the modern solutions of process control. The proposed described methods are illustrated by various case studies for the main industrial sectors

There exist a number of books related each one to a single type of control, yet usually without comparisons for various industrial sectors. Some other books present modelling and identification methods or signal processing. This book presents the methods to solve all the problems linked to the design of a process control without the need to find additional information.

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