Robust Stability of Constrained Model Predictive Control

Abstract

A new design technique for a robust model predictive controller is proposed using an uncertainty description expressed in the time-domain. Robust stability of the resulting closed-loop system is guaranteed for a set of Finite Impulse Response (FIR) models. Both necessary and sufficient conditions for asymptotic stability are stated. If the uncertainty is described as lower and upper bounds on impulse response coefficients, then the resulting optimization problem can be cast as a linear program of moderate size.

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