Rigid Tube Model Predictive Control for Linear Sampled–data Systems

摘要

We consider the problem of robust model predictive control for linear sampled– data dynamical systems subject to state and control constraints and additive and bounded disturbances. We propose a rigid tube model predictive control algorithm utilizing recent and topologically compatible notions for the sampled–data forward reach sets as well as robust positively invariant sets. The proposed method inherits almost all desirable features associated with rigid tube model predictive control of discrete-time systems, and, in addition, it ensures robust constraint satisfaction and safety in a continuous-time sense.