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In this paper, a state-dependent control updating period framework isproposed that leads to real-time implementable Model Predictive Control withcertified practical stability results and constraints satisfaction. The schemeis illustrated and validated using new certification bound that is derived inthe case where the Fast Gradient iteration is used through a penalty method tosolve generally constrained convex optimization problems. Both thecertification bound computation and its use in the state-dependent updatingperiod framework are illustrated in the particular case of linear MPC. Anillustrative example involving a chain of four integrators is used to show theexplicit computation of the state-dependent control updating scheme.

A State-Dependent Updating Period For Certified Real-Time Model Predictive Control