%T A model predictive control approach for stochastic networked control systems
%R 10.3182/20100913-2-FR-4014.00007
%B 2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems
%I IFAC
%L eprints734
%X 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.
%A Daniele Bernardini
%A M.C.F. Donkers
%A Alberto Bemporad
%A W.P.M.H. Heemels
%D 2010