This article builds the theoretical foundations for dynamic mode decomposition (DMD) of
control-affine dynamical systems by leveraging the theory of vector-valued reproducing …

This article investigates the cooperative estimation problem to recover the parametric flow
field through sensor measurements from an autonomous underwater vehicle (AUV) team …

Localization measurements for an autonomous underwater vehicle (AUV) are often difficult
to obtain. In many cases, localization measurements are only available sporadically after the …

This manuscript is aimed at addressing several long-standing limitations of dynamic mode
decomposition in the application of Koopman analysis. Principal among these limitations are …

In this article, an adaptive nonparametric method is proposed to estimate the unknown
scalar-valued function that appears in systems governed by ordinary differential equations …

Learning a nonparametric system of ordinary differential equations from trajectories in a d-
dimensional state space requires learning d functions of d variables. Explicit formulations …

Modern data science problems revolves around the Koopman operator C φ (or Composition
operator) approach, which provides the best-fit linear approximator to the dynamical system …

This paper focus on a distributed method for three-dimensional flow field estimation using
multiple autonomous underwater vehicles (AUVs). In this method, direct measurements of …

Learning a nonparametric system of ordinary differential equations (ODEs) from $ n $
trajectory snapshots in a $ d $-dimensional state space requires learning $ d $ functions of …

Conventionally, data driven identification and control problems for higher order dynamical
systems are solved by augmenting the system state by the derivatives of the output to …