Modern Predictive Control
eBook - ePub

Modern Predictive Control

  1. 286 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Modern Predictive Control

About this book

Modern Predictive Control explains how MPC differs from other control methods in its implementation of a control action. Most importantly, MPC provides the flexibility to act while optimizing—which is essential to the solution of many engineering problems in complex plants, where exact modeling is impossible.

The superiority of MPC is in its numerical solution. Usually, MPC is employed to solve a finite-horizon optimal control problem at each sampling instant and obtain control actions for both the present time and a future period. However, only the current control move is applied to the plant.

This complete, step-by-step exploration of various approaches to MPC:

  • Introduces basic concepts of systems, modeling, and predictive control, detailing development from classical MPC to synthesis approaches
  • Explores use of Model Algorithmic Control (MAC), Dynamic Matrix Control (DMC), Generalized Predictive Control (GPC), and Two-Step Model Predictive Control
  • Identifies important general approaches to synthesis
  • Discusses open-loop and closed-loop optimization in synthesis approaches
  • Covers output feedback synthesis approaches with and without a finite switching horizon

This book gives researchers a variety of models for use with one- and two-step control. The author clearly explains the variations between predictive control methods—and the root of these differences—to illustrate that there is no one ideal MPC and that one should remain open to selecting the best possible model in each unique circumstance.

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Yes, you can access Modern Predictive Control by Ding Baocang in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Electrical Engineering & Telecommunications. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. Abstract
  7. Preface
  8. 1 Systems, modeling and model predictive control
  9. 2 Model algorithmic control (MAC)
  10. 3 Dynamic matrix control (DMC)
  11. 4 Generalized predictive control (GPC)
  12. 5 Two-step model predictive control
  13. 6 Sketch of synthesis approaches of MPC
  14. 7 State feedback synthesis approaches
  15. 8 Synthesis approaches with finite switching horizon
  16. 9 Open-loop optimization and closed-loop optimization in synthesis approaches
  17. 10 Output feedback synthesis approaches
  18. Bibliography
  19. Index