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Explicit robust multi–parametric feedback control laws are designed for constrained dynamic systems involving uncertainty in the left-hand side(LHS) of the underlying MPC optimization model. Our proposed procedure features: (i) a robust reformulation/optimization step, (ii) a dynamic programming framework for the model predictive control (MPC) problem(More)
In this paper we present a framework for robust explicit/multi–parametric model predictive control (MPC). Based on four key steps, the proposed framework offers a systematic method for the off–line design, validation/testing and implementation of robust explicit MPC controllers for embedded systems. An important feature of the framework, is the use of a(More)
Robust explicit/multi-parametric controllers are designed for constrained, linear discrete–time systems with box-constrained states and inputs, involving uncertainty in the left–hand side (LHS) of the Model Predictive Control (MPC) optimization model. Based on previous results, this work presents a new algorithm that features: (i) a dynamic programming(More)
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