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
@article{TarDeS:09-024,
author = {Tar{\u{a}}u, Alina N. and De Schutter, Bart and Hellendoorn,
Johannes},
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}
}