Publication
Multi-layer decentralized MPC of large-scale networked systems
Book Chapter (2014)
Book Title
Distributed Model Predictive Control Made Easy
Publisher
Springer
Pages
495-515
Volume
69
Number
31
Serie
Intelligent Systems, Control and Automation: Science and Engineering
Doc link
http://link.springer.com/chapter/10.1007/978-94-007-7006-5_31
File
Authors
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Ocampo Martínez, Carlos A.
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Puig Cayuela, Vicenç
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Grosso Pérez, Juan Manuel
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Montes de Oca, Saúl
Projects associated
Abstract
In this chapter, a multi-layer decentralized model predictive control (ML- DMPC) approach is proposed and designed for its application to large-scale net- worked systems (LSNS). This approach is based on the periodic nature of the sys- tem disturbance and the availability of both static and dynamic models of the LSNS. Hence, the topology of the controller is structured in two layers. First, an upper layer is in charge of achieving the global objectives from a set O of control objectives given for the LSNS. This layer works with a sampling time ∆t1, corresponding to the disturbances period. Second, a lower layer, with a sampling time ∆t2, ∆t1 > ∆t2, is in charge of computing the references for the system actuators in order to satisfy the local objectives from the set of control objectives O. A system partitioning al- lows to establish a hierarchical flow of information between a set C of controllers designed based on model predictive control (MPC). Therefore, the whole proposed ML-DMPC strategy results in a centralized optimization problem for considering the global control objectives, followed of a decentralized scheme for reaching the local control objectives. The proposed approach is applied to a real case study: the water transport network of Barcelona (Spain). Results obtained with selected simu- lation scenarios show the effectiveness of the proposed ML-DMPC strategy in terms of system modularity, reduced computational burden and, at the same time, the ad- missible loss of performance with respect to a centralized MPC (CMPC) strategy.
Categories
control system synthesis, linear programming, optimisation, predictive control.
Author keywords
decentralised control, model predictive control, non-iterative control topologies, industrial applications, partitioning
Scientific reference
C. Ocampo-Martínez, V. Puig, J.M. Grosso and S. Montes. Multi-layer decentralized MPC of large-scale networked systems. In Distributed Model Predictive Control Made Easy, 495-515. Springer, 2014.
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