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The paper deals with the predictive control for linear systems subject to constraints, technique which leads to nonlinear (piecewise affine) control laws. The main goal is to reduce the sensitivity of these schemes with respect to the model uncertainties and avoid in the same time a fastidious on-line optimisation which may reduce the range of application. In this idea a two stage predictive strategy is proposed, which synthesizes 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 noise model.

OFF-LINE ROBUSTIFICATION OF EXPLICIT MPC LAWS - The Case of Polynomial Model Representation