Distributed MPC Under Coupled Constraints Based on Dantzig-Wolfe Decomposition

In this chapter, we propose a distributed model predictive control scheme based on the Dantzig-Wolfe decomposition to control a collection of linear dynamical systems coupled by linear global constraints. The resulting structure is composed of one optimiz

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José M. Maestre Rudy R. Negenborn Editors

Distributed Model Predictive Control Made Easy

Intelligent Systems, Control and Automation: Science and Engineering Volume 69

Editor S. G. Tzafestas, National Technical University of Athens, Athens, Greece Editorial Advisory Board P. Antsaklis, University of Notre Dame, Dame, IN, U.S.A. P. Borne, Ecole Centrale de Lille, Villeneuve-d’Ascq, France D. G. Caldwell, University of Salford, Salford, U.K. C. S. Chen, University of Akron, Akron, OH, U.S.A. T. Fukuda, Nagoya University, Nagoya, Japan S. Monaco, University La Sapienza, Rome, Italy G. Schmidt, Technical University of Munich, Munich, Germany S. G. Tzafestas, National Technical University of Athens, Athens, Greece F. Harashima, University of Tokyo, Tokyo, Japan N. K. Sinha, McMaster University, Hamilton, ON, Canada D. Tabak, George Mason University, Fairfax, VA, U.S.A. K. Valavanis, University of Denver, Denver, Colorado, U.S.A.

For further volumes: http://www.springer.com/series/6259

José M. Maestre Rudy R. Negenborn •

Editors

Distributed Model Predictive Control Made Easy

123

Editors José M. Maestre Department of Systems and Automation Engineering University of Seville Seville Spain

ISSN 2213-8986 ISBN 978-94-007-7005-8 DOI 10.1007/978-94-007-7006-5

Rudy R. Negenborn Department of Marine and Transport Technology Delft University of Technology Delft The Netherlands

ISSN 2213-8994 (electronic) ISBN 978-94-007-7006-5 (eBook)

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