Editors:
- A systematic, practical, and accessible approach to distributed (and hierarchical) model predictive control (MPC)
- Provides step-by-step descriptions of computations/equations; theoretical results; and applications
- A consistent description of all approaches enables readers to assess the usefulness of these approaches for their respective applications
Part of the book series: Intelligent Systems, Control and Automation: Science and Engineering (ISCA, volume 69)
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Table of contents (36 chapters)
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Front Matter
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From Small-Scale to Large-Scale: The Group of Autonomous Systems Perspective
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Front Matter
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About this book
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.
Reviews
From the reviews:
“This book presents a modern solution for the control and monitoring of complex structures using distributed control systems based on high-level communication protocols dedicated to control applications. … this book will be particularly interesting to readers in academia and research who wish to acquire a theoretical knowledge base and identify new areas of research. … practitioners may find it a useful handbook to assist in current projects.” (Eugen Petac, Computing Reviews, February, 2014)Editors and Affiliations
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Systems Engineering and Automation Dept, University of Seville, Seville, Spain
José M. Maestre
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Dept of Marine & Transport Technology, Delft University of Technology, Delft, The Netherlands
Rudy R. Negenborn
Bibliographic Information
Book Title: Distributed Model Predictive Control Made Easy
Editors: José M. Maestre, Rudy R. Negenborn
Series Title: Intelligent Systems, Control and Automation: Science and Engineering
DOI: https://doi.org/10.1007/978-94-007-7006-5
Publisher: Springer Dordrecht
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Science+Business Media Dordrecht 2014
Hardcover ISBN: 978-94-007-7005-8Published: 25 November 2013
Softcover ISBN: 978-94-024-0714-3Published: 18 September 2016
eBook ISBN: 978-94-007-7006-5Published: 10 November 2013
Series ISSN: 2213-8986
Series E-ISSN: 2213-8994
Edition Number: 1
Number of Pages: XVIII, 600
Number of Illustrations: 138 b/w illustrations
Topics: Control and Systems Theory, Vibration, Dynamical Systems, Control, Systems Theory, Control, Organization, Simulation and Modeling