Centralized, Decentralized, and Distributed Model Predictive Control
for Route Choice in Automated Baggage Handling Systems
Reference
A.N. Tarău,
B. De Schutter, and
J. Hellendoorn,
"Centralized, Decentralized, and Distributed Model Predictive Control
for Route Choice in Automated Baggage Handling Systems," Control Engineering and Applied Informatics, Special
Issue on Distributed Control in Networked Systems, vol. 11, no. 3, pp.
24-31, 2009.
Abstract
In this paper we develop and compare efficient predictive control
methods for routing individual vehicles which ensure automatic
transportation of bags in a baggage handling system of an airport. In
particular we consider centralized, decentralized, and distributed
model predictive control (MPC). To assess the performance of the
proposed control approaches, we consider a simple benchmark case
study, in which the methods are compared for several scenarios. The
results indicate that the best performance of the system is obtained
when using centralized MPC. However, centralized MPC becomes
intractable when the number of junctions is large due to the high
computational effort this method requires. Decentralized and
distributed MPC offer a balanced trade-off between computation time
and optimality.
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Bibtex entry
@article{TarDeS:09-024,
author={A.N. Tar{\u{a}}u and B. {D}e Schutter and J. Hellendoorn},
title={Centralized, Decentralized, and Distributed Model Predictive Control for
Route Choice in Automated Baggage Handling Systems},
journal={Control Engineering and Applied Informatics, \textnormal{Special Issue
on Distributed Control in Networked Systems}},
volume={11},
number={3},
pages={24--31},
year={2009}
}
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