Robust tube-based model predictive control with Koopman operators

Koopman operators are of infinite dimension and capture the characteristics nonlinear dynamics in a lifted global linear manner. The finite data-driven approximation results class predictors, useful for formulating model predictive control (MPC) dynamical systems with reduced computational complexity. However, robustness closed-loop MPC under modeling errors possible exogenous disturbances is still crucial issue to be resolved. Aiming at above problem, this paper presents robust tube-based solution operators, i.e., r-KMPC, discrete-time additive disturbances. proposed controller composed nominal using an off-line feedback policy. approach does not assume convergence approximated operator, which allows limited order design. Fundamental properties, e.g., stabilizability, observability, derived standard assumptions which, point-wise proven. Simulated examples illustrated verify effectiveness approach.