TY  - CHAP
N2  - 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.
UR  - http://www.ifac-papersonline.net/Detailed/44627.html
TI  - A model predictive control approach for stochastic networked control systems
ID  - eprints734
AV  - none
A1  - Bernardini, Daniele
A1  - Donkers, M.C.F.
A1  - Bemporad, Alberto
A1  - Heemels, W.P.M.H.
T2  - 2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems
Y1  - 2010///
EP  - 6
PB  - IFAC
SN  - 978-3-902661-82-1
ER  -