eprintid: 725
rev_number: 17
eprint_status: archive
userid: 7
dir: disk0/00/00/07/25
datestamp: 2011-07-27 12:51:25
lastmod: 2011-08-05 11:12:37
status_changed: 2011-07-27 12:51:25
type: article
metadata_visibility: show
item_issues_count: 0
creators_name: Alessio, Alessandro
creators_name: Barcelli, Davide
creators_name: Bemporad, Alberto
creators_id: 
creators_id: 
creators_id: alberto.bemporad@imtlucca.it
title: Decentralized model predictive control of dynamically coupled linear systems
ispublished: pub
subjects: QA
subjects: QA75
subjects: TJ
divisions: CSA
full_text_status: none
keywords: Model predictive control; Decentralized control; Multi-layer control; Networked control; Packet loss
note: Special Issue on Hierarchical and Distributed Model Predictive Control
abstract: This paper proposes a decentralized model predictive control (DMPC) scheme for large-scale dynamical processes subject to input constraints. The global model of the process is approximated as the decomposition of several (possibly overlapping) smaller models used for local predictions. The degree of decoupling among submodels represents a tuning knob of the approach: the less coupled are the submodels, the lighter the computational burden and the load for transmission of shared information; but the smaller is the degree of cooperativeness of the decentralized controllers and the overall performance of the control system. Sufficient criteria for analyzing asymptotic closed-loop stability are provided for input constrained open-loop asymptotically stable systems and for unconstrained open-loop unstable systems, under possible intermittent lack of communication of measurement data between controllers. The DMPC approach is also extended to asymptotic tracking of output set-points and rejection of constant measured disturbances. The effectiveness of the approach is shown on a relatively large-scale simulation example on decentralized temperature control based on wireless sensor feedback.
date: 2011-06
date_type: published
publication: Journal of Process Control
volume: 21
number: 5
publisher: Elsevier
pagerange: 705 - 714
id_number: 10.1016/j.jprocont.2010.11.003 
refereed: TRUE
issn: 0959-1524
official_url: http://www.sciencedirect.com/science/article/pii/S0959152410002210
citation:   Alessio, Alessandro and Barcelli, Davide and Bemporad, Alberto  Decentralized model predictive control of dynamically coupled linear systems.  Journal of Process Control, 21 (5).  705 - 714.  ISSN 0959-1524      (2011)