Distributed Model Predictive Control Made Easy

José M. Maestre (u. a.)

ISBN 10: 9402407146 / ISBN 13: 9789402407143

Published by Springer, 2016

About this Item

Distributed Model Predictive Control Made Easy | José M. Maestre (u. a.) | Taschenbuch | Intelligent Systems, Control and Automation: Science and Engineering | xviii | Englisch | 2016 | Springer | EAN 9789402407143 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Seller Inventory # 103327087

Bibliographic Details

• Title: Distributed Model Predictive Control Made Easy
• Publisher: Springer
• Publication Date: 2016
• Language: English
• ISBN 10: 9402407146
• ISBN 13: 9789402407143
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 34D millimeters 235 millimeters width by 155 millimeters height by 34 millimeters depth
• Weight: 925 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems.

This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those who want to gain a deeper insight in the wide range of distributed MPC techniques available.