@incollection{eprints734,
          author = {Daniele Bernardini and M.C.F. Donkers and Alberto Bemporad and W.P.M.H. Heemels},
            year = {2010},
           title = {A model predictive control approach for stochastic networked control systems},
       booktitle = {2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems},
       publisher = {IFAC},
        abstract = {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.},
             url = {http://eprints.imtlucca.it/734/}
}