@incollection{eprints431,
           pages = {204--209},
         address = {24th Sep. - 26th Sep. 2009},
            year = {2009},
           title = {Decentralized model predictive control of dynamically-coupled linear systems: tracking under packet loss},
          author = {Davide Barcelli and Alberto Bemporad},
         journal = {Estimation and Control of Networked Systems},
       publisher = {IFAC},
       booktitle = {Estimation and Control of Networked Systems},
        abstract = {For large-scale processes whose dynamics can be represented as the interaction of several dynamically-coupled linear subsystems, this paper proposes a decentralized model predictive control (MPC) design approach for set-point tracking under input constraints and possible loss of information packets. Following earlier results in (Alessio and Bemporad, 2007 and 2008), the global model of the process is approximated as the decomposition of several (possibly overlapping) smaller models used for local predictions. We present sufficient criteria for asymptotic tracking of output set-points and rejection of constant measured disturbances when the overall process is in closed loop with the set of decentralized MPC controllers, under possible intermittent lack of communication of measurement data between controllers. The effectiveness of the approach is shown in a simulation example on distributed temperature control in the passenger area of a railcar.},
             url = {http://eprints.imtlucca.it/431/},
        keywords = {Decentralized and cooperative optimization; Coordinated control and estimation over networks}
}