On robustness properties of constrained receding-horizon controllers

Receding-horizon predictive control has proven to be a flexible and effective method for controlling industrial plants, as witnessed by its widespread adoption in petrochemical industry. However, it is well known that a plain receding-horizon strategy does not guarantee closed-loop stability. One can achieve stability by complementing the finite-horizon cost functional with terminal constraints on the state at the end of the optimization horizon. This notion of constrained receding-horizon control (CRH) is playing a major role in the development of predictive controllers with guaranteed stability. Furthermore, the stabilizing properties of the CRH strategy hold also for nonlinear systems. The authors investigate the robust stability of nonlinear systems controlled according to a CRH strategy. The robustness is analogous to that of types of optimal control