Robust Nonlinear Model Predictive Control With Variable Block Length

Robust model predictive controllers for discrete-time nonlinear systems are proposed in this technical note. The algorithms first search for an open-loop controller with some block length, and then try to improve it in a closed-loop fashion by solving minimax problems on-line. It is proved that the controllers are capable of making a subsequence of the state converge into a target set in the presence of bounded disturbances.