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A model predictive control approach for stochastic networked control systems

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)

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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.

Item Type: Book Section
Identification Number: 10.3182/20100913-2-FR-4014.00007
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TJ Mechanical engineering and machinery
Research Area: Computer Science and Applications
Depositing User: Professor Alberto Bemporad
Date Deposited: 29 Jul 2011 10:18
Last Modified: 16 Nov 2011 11:50
URI: http://eprints.imtlucca.it/id/eprint/734

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