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Optimal construction of Koopman eigenfunctions for prediction and control
Milan Korda, Igor Mezić
This work presents a novel data-driven framework for constructing eigenfunctions of the Koopman operator geared toward prediction and control. The method leverages the richness of…
Convex computation of extremal invariant measures of nonlinear dynamical systems and Markov processes
Milan Korda, Didier Henrion, Igor Mezic
We propose a convex-optimization-based framework for computation of invariant measures of polynomial dynamical systems and Markov processes, in discrete and continuous time. The se…
On Convergence of Extended Dynamic Mode Decomposition to the Koopman Operator
Milan Korda, Igor Mezić
Extended Dynamic Mode Decomposition (EDMD) is an algorithm that approximates the action of the Koopman operator on an -dimensional subspace of the space of observables by sampli…
Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control
Milan Korda, Igor Mezić
This paper presents a class of linear predictors for nonlinear controlled dynamical systems. The basic idea is to lift the nonlinear dynamics into a higher dimensional space where…