We develop a data-driven, model-free approach for the optimal control of the dynamical
system. The proposed approach relies on the Deep Neural Network (DNN) based learning …

We propose a novel operator-theoretic framework to study global stability of nonlinear
systems. Based on the spectral properties of the so-called Koopman operator, our approach …

We address the long-standing problem of computing the region of attraction (ROA) of a
target set (eg, a neighborhood of an equilibrium point) of a controlled nonlinear system with …

In this paper we develop a new approach for observer synthesis for discrete time
autonomous nonlinear systems based on Koopman operator theoretic framework. Koopman …

We propose a new observer form based on Koopman operator theoretic framework for input-
output nonlinear systems with control affine inputs. Based on this observer form, we describe …

In this paper, we provide a systematic approach for the design of stabilizing feedback
controllers for nonlinear control systems using the Koopman operator framework. The …

Abstract The Koopman and Perron Frobenius transport operators are fundamentally
changing how we approach dynamical systems, providing linear representations for even …

Transient stability control of power systems is based on actions that are taken automatically
following a disturbance to ensure that the system remains in synchronism. Examples of such …

In the paper, we consider the problem of robust approximation of transfer Koopman and
Perron–Frobenius (P–F) operators from noisy time-series data. In most applications, the time …

We present data-driven methods for power system transient stability analysis using a unit
eigenfunction of the Koopman operator. We show that the Koopman eigenfunction with unit …