@article{eprints489,
           title = {Robust explicit MPC based on approximate multi-parametric convex programming},
            year = {2006},
           month = {August},
          volume = {51},
           pages = {1399--1403},
          number = {8},
       publisher = {IEEE},
         journal = {IEEE Transactions on Automatic Control },
          author = {David Mu{\~n}oz de la Pe{\~n}a and Alberto Bemporad and Carlo Filippi},
        abstract = {Many robust model predictive control (MPC) schemes require the online solution of a computationally demanding convex program. For deterministic MPC schemes, multiparametric programming was successfully applied to move offline most of the computation. In this paper, we adopt a general approximate multiparametric algorithm recently suggested for convex problems and propose to apply it to a classical robust MPC scheme. This approach enables one to implement a robust MPC controller in real time for systems with polytopic uncertainty, ensuring robust constraint satisfaction and robust convergence to a given bounded set},
             url = {http://eprints.imtlucca.it/489/},
        keywords = {multiparametric programming; polytopic uncertainty; robust constraint satisfaction; robust convergence; robust model predictive control schemes; uncertain systems; convex programming; predictive control; robust control; uncertain systems}
}