Abstract
The paper deals with the predictive control for linear systems subject to constraints, leading to piecewise affine control laws. The main goal is to reduce the sensitivity of these schemes with respect to the model uncertainties. This objective can be attained by considering worst-case (min-max) formulations, but generally this is leading to fastidious on-line optimisation which may reduce the range of application. Here a two stage predictive strategy is proposed, which synthesize in a first instant an analytical (continuous and piecewise linear) control law based on the nominal model and secondly robustify the central controller (the controller obtained when no constraint is active). This robustification is then expanded to all the space of the piecewise structure by means of its corresponding disturbance model.
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