Web Reference: Jan 1, 2026 · This survey provides a systematic overview of Koopman-based control, emphasizing the connection between data-driven surrogate models, approximation errors, controller design, and closed-loop guarantees. (Koopman operator) Let \(X_t\) satisfy (SDE) for \(t \ge 0\). The Koopman operator semigroup associated with (SDE) is defined by for all bounded measurable functions f. In case of ergodic sampling, that is, obtaining data points from a single long trajectory, we will assume invariance of the measure \(\mu \) w.r.t. the stochastic process \(X_t\). Abstract stems, many data-driven control methods rely on the behavio tem to predi hen the noise is bounded, we propose a method for designing histo utation of an upper bound on the prediction error. This approach allows us a minmax control problem where robust constraint satisfaction is enforced. We derive an upper bound ality gap of the resul
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