Centralized, decentralized, and distributed model predictive control for route choice in automated baggage handling systems

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.