A Finite-Gain Stability Approach to NMPC Design

This paper proposes a novel approach to the design of Nonlinear Model Predictive Control (NMPC) schemes based on the Finite-Gain Stability (FGS) concept. The proposed formulation considers the case where the plant is affected by unknown but bounded disturbances, which renders the classical Lyapunov-based analysis/design difficult. Based on FGS conditions for a closed-loop system, we develop a systematic scenario-based NMPC design methodology, allowing us to choose the relevant NMPC parameters enforcing FGS and providing satisfactory tracking performance. A simulated example is presented to demonstrate the effectiveness of our framework.