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Model Predictive Control

Model Predictive Control

Model Predictive Control
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Model Predictive Control Hardback - 2024

by Baocang Ding

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Details

  • Title Model Predictive Control
  • Author Baocang Ding
  • Binding Hardback
  • Condition New
  • Pages 304
  • Volumes 1
  • Language ENG
  • Publisher Wiley-IEEE Press
  • Publication date 2024-03-25
  • Features Bibliography, Index
  • Bookseller's Inventory # 29967462
  • ISBN 9781119471394 / 1119471397
  • Weight 1.49 lbs (0.68 kg)
  • Dimensions 9.61 x 6.69 x 0.69 in (24.41 x 16.99 x 1.75 cm)
  • Category Science
  • Library of Congress subjects Predictive control
  • Library of Congress Catalogue Number 2023049301
  • Dewey Decimal Code 629.8
  • Quantity available 5

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Reader reviews for Model Predictive Control

From the publisher

Model Predictive Control

Understand the practical side of controlling industrial processes

Model Predictive Control (MPC) is a method for controlling a process according to given parameters, derived in many cases from empirical models. It has been widely applied in industrial units to increase revenue and promoting sustainability. Systematic overviews of this subject, however, are rare, and few draw on direct experience in industrial settings.

Assuming basic knowledge of the relevant mathematical and algebraic modeling techniques, the book's title combines foundational theories of MPC with a thorough sense of its practical applications in an industrial context. The result is a presentation uniquely suited to rapid incorporation in an industrial workplace.

Model Predictive Control readers will also find:

  • Two-part organization to balance theory and applications
  • Selection of topics directly driven by industrial demand
  • An author with decades of experience in both teaching and industrial practice

This book is ideal for industrial control engineers and researchers looking to understand MPC technology, as well as advanced undergraduate and graduate students studying predictive control and related subjects.

From the rear cover

Understand the practical side of controlling industrial processes

Model Predictive Control (MPC) is a method for controlling a process according to given parameters, derived in many cases from empirical models. It has been widely applied in industrial units to increase revenue and promoting sustainability. Systematic overviews of this subject, however, are rare, and few draw on direct experience in industrial settings.

Assuming basic knowledge of the relevant mathematical and algebraic modeling techniques, the book's title combines foundational theories of MPC with a thorough sense of its practical applications in an industrial context. The result is a presentation uniquely suited to rapid incorporation in an industrial workplace.

Model Predictive Control readers will also find:

  • Two-part organization to balance theory and applications
  • Selection of topics directly driven by industrial demand
  • An author with decades of experience in both teaching and industrial practice

This book is ideal for industrial control engineers and researchers looking to understand MPC technology, as well as advanced undergraduate and graduate students studying predictive control and related subjects.

About the author

Baocang Ding, PhD, teaches MPC to both undergraduate and graduate students in the School of Automation, Chongqing University of Posts and Telecommunications, China. His research interests include model predictive control, control of power network, process control, and control software development.

Yuanqing Yang, PhD, teaches MPC to both undergraduate and graduate students in the School of Automation, Chongqing University of Posts and Telecommunications, China. His research interests include model predictive control, fuzzy control, networked control, and distributed control systems.

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