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Distributed model predictive control based on a cooperative game
Author(s) -
Maestre J. M.,
Muñoz de la Peña D.,
Camacho E. F.
Publication year - 2011
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.940
Subject(s) - computer science , scheme (mathematics) , model predictive control , stability (learning theory) , mathematical optimization , state (computer science) , control (management) , controller (irrigation) , game theory , order (exchange) , control theory (sociology) , distributed computing , artificial intelligence , mathematics , mathematical economics , machine learning , algorithm , mathematical analysis , finance , economics , biology , agronomy
Abstract In this work we propose a distributed model predictive control scheme based on a cooperative game in which two different agents communicate in order to find a solution to the problem of controlling two constrained linear systems coupled through the inputs. We assume that each agent only has partial information of the model and the state of the system. In the proposed scheme, the agents communicate twice each sampling time in order to share enough information to take a cooperative decision. We provide sufficient conditions that guarantee practical stability of the closed‐loop system as well as an optimization‐based procedure to design the controller so that these conditions are satisfied. The theoretical results and the design procedure are illustrated using two different examples. Copyright © 2010 John Wiley & Sons, Ltd.