We present a method to design a state-feedback controller ensuring exponential stability for
nonlinear systems using only measurement data. Our approach relies on Koopman-operator …

Dynamic mode decomposition (DMD) and its variants, such as extended DMD (EDMD), are
broadly used to fit simple linear models to dynamical systems known from observable data …

We propose a Markov Chain Monte Carlo (MCMC) algorithm based on Gibbs sampling with
parallel tempering to solve nonlinear optimal control problems. The algorithm is applicable …

We introduce a method for constructing reduced-order models directly from videos of
dynamical systems. The method uses a non-intrusive tracking to isolate the motion of a user …

While linear systems are well-understood, no explicit solution exists for general nonlinear
systems. Thus, it is desirable to make the understanding of linear system available in the …

We propose a Markov Chain Monte Carlo (MCMC) algorithm based on Gibbs sampling with
parallel tempering to solve nonlinear optimal control problems. The algorithm is applicable …

The Koopman operator provides a linear perspective on non-linear dynamics by focusing on
the evolution of observables in an invariant subspace. Observables of interest are typically …