Robust Model Predictive Control of continuous-time sampled-data nonlinear systems with Integral Sliding Mode

A hierarchical Nonlinear Model Predictive Control (NMPC) scheme with guaranteed Input-to-State-practical-Stability (ISpS) is proposed. The controller is formed by an Integral Sliding Mode (ISM) controller and a NMPC one. The ISM, relying on the knowledge of the nominal continuous-time model of the system and of the piecewise constant control signal generated by the NMPC produces a control action aimed at reducing the difference between the dynamics of the nominal closed-loop system and the actual evolution of the state. The NMPC in this way can be designed based on a system with reduced uncertainty. In order to prove the stability of the overall control scheme, some general Regional ISpS results for continuous-time systems are proven.