@article{eprints3583,
           pages = {3292--3310},
       publisher = {Wiley},
          number = {15},
          volume = {26},
           title = {Real-time model predictive control based on dual gradient projection: Theory and fixed-point FPGA implementation},
            year = {2016},
          author = {Matteo Rubagotti and Panagiotis Patrinos and Alberto Guiggiani and Alberto Bemporad},
         journal = {International Journal of Robust and Nonlinear Control},
        abstract = {This paper proposes a method to design robust model predictive control (MPC) laws for discrete-time linear systems with hard mixed constraints on states and inputs, in case of only an inexact solution of the associated quadratic program is available, because of real-time requirements. By using a recently proposed dual gradient-projection algorithm, it is proved that the discrepancy of the optimal control law as compared with the obtained one is bounded even if the solver is implemented in fixed-point arithmetic. By defining an alternative MPC problem with tightened constraints, a feasible solution is obtained for the original MPC problem, which guarantees recursive feasibility and asymptotic stability of the closed-loop system with respect to a set including the origin, also considering the presence of external disturbances. The proposed MPC law is implemented on a field-programmable gate array in order to show the practical applicability of the method.},
             url = {http://eprints.imtlucca.it/3583/}
}