@incollection{eprints591,
          author = {Alberto Bemporad and Edoardo Mosca},
         journal = {Proc. 34th IEEE Conf. on Decision and Control},
       publisher = {IEEE},
       booktitle = {Decision and Control Conference},
         address = {New Orleans, December 1995},
           pages = {1205--1210},
          volume = {2},
            year = {1995},
           title = {Nonlinear predictive reference governor for constrained control systems},
        abstract = {This paper presents a new methodology for solving control problems where hard contraints on the state and/or the inputs of the system are present. This is achieved by adding to the control architecture a command governor which prefilters the reference to be tracked, taking into account the current value of the state and aiming at optimizing a tracking performance index. The overall system is proved to be asymptotically stable, and feasibility is ensured by a weak condition on the initial state linear loops, a complete solution is developed for the latter. The resulting online computational burden turns out to be moderate and the related operations executable with current low-priced computing hardware},
             url = {http://eprints.imtlucca.it/591/},
        keywords = {asymptotic stability; computational complexity; filtering theory; nonlinear control systems; performance index; predictive control
}
}