Linearity of Koopman operators and simplicity of their estimators coupled with model-
reduction capabilities has lead to their great popularity in applications for learning dynamical …

The purpose of perimeter control is to regulate the transfer flow between the perimeters of
the urban traffic network, so that the vehicle aggregation in each region is maintained at a …

We use Koopman theory to develop a data-driven nonlinear model reduction and
identification strategy for multiple-input multiple-output (MIMO) input-affine dynamical …

Sparked by the Willems' fundamental lemma, a class of data-driven control methods has
been developed for LTI systems. At the same time, the Koopman operator theory attempts to …

This paper proposes a fully data-driven approach for optimal control of nonlinear control-
affine systems represented by a stochastic diffusion. The focus is on the scenario where both …

The modeling of microbial fed-batch fermentation with switching operators to product 1, 3-
propanediol (1, 3-PD) still maintains a challenge because it is strongly of nonlinearity and …

In this paper, we present an approach based on the spectral analysis of the Koopman
operator for the approximate solution of the Hamilton Jacobi equation that arises while …

In this article, we provide a data-driven framework for optimal control of a continuous-time
control-affine stochastic dynamical system. The proposed framework relies on the linear …

This paper presents a novel approach for optimal control of nonlinear stochastic systems
using infinitesimal generator learning within infinite-dimensional reproducing kernel Hilbert …

This paper provides a tutorial on how to use Koopman operators to lift Pontryagin's
optimality condition for infinite-horizon optimal control problems into an infinite dimensional …