relation: http://eprints.imtlucca.it/734/
title: A model predictive control approach for stochastic networked control systems
creator: Bernardini, Daniele
creator: Donkers, M.C.F.
creator: Bemporad, Alberto
creator: Heemels, W.P.M.H.
subject: QA75 Electronic computers. Computer science
subject: TJ Mechanical engineering and machinery
description: In this paper we present a stochastic model predictive control (SMPC) approach for networked control systems (NCSs) that are subject to time-varying sampling intervals and time-varying transmission delays. These network-induced uncertain parameters are assumed to be described by random processes, having a bounded support and an arbitrary continuous probability density function. Assuming that the controlled plant can be modeled as a linear system, we present a SMPC formulation based on scenario enumeration and quadratic programming that optimizes a stochastic performance index and provides closed-loop stability in the mean-square sense. Simulation results are shown to demonstrate the performance of the proposed approach.
publisher: IFAC
date: 2010
type: Book Section
type: PeerReviewed
identifier:   Bernardini, Daniele and Donkers, M.C.F. and Bemporad, Alberto and Heemels, W.P.M.H.  A model predictive control approach for stochastic networked control systems.   In:  2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems.   IFAC.  ISBN 978-3-902661-82-1      (2010)  
relation: http://www.ifac-papersonline.net/Detailed/44627.html
relation: 10.3182/20100913-2-FR-4014.00007