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This paper presents a novel formulation of a robust model predictive controller (RMPCT) to track piecewise constant references. The real plant is assumed to be modelled as a linear system with additive bounded uncertainties on the states. Under mild assumptions, the proposed MPC can steer the uncertain system in an admissible evolution to any admissible steady state, that is, under any change of the...
This paper deals with the application of a model predictive controller (MPC) for tracking to a real system: a linear motor. The MPC formulation used in this paper in a novel approach to track piecewise constant references recently presented by the authors. The main novelties of this controller are: (i) the addition of an artificial steady state and input as decision variables, (ii) the minimization...
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