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Deep learning of Koopman representation for control
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 …
system. The proposed approach relies on the Deep Neural Network (DNN) based learning …
Global stability analysis using the eigenfunctions of the Koopman operator
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 …
systems. Based on the spectral properties of the so-called Koopman operator, our approach …
Convex computation of the region of attraction of polynomial control systems
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 …
target set (eg, a neighborhood of an equilibrium point) of a controlled nonlinear system with …
Linear observer synthesis for nonlinear systems using Koopman operator framework
In this paper we develop a new approach for observer synthesis for discrete time
autonomous nonlinear systems based on Koopman operator theoretic framework. Koopman …
autonomous nonlinear systems based on Koopman operator theoretic framework. Koopman …
Koopman operator based observer synthesis for control-affine nonlinear systems
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 …
output nonlinear systems with control affine inputs. Based on this observer form, we describe …
Real power modulation strategies for transient stability control
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 …
following a disturbance to ensure that the system remains in synchronism. Examples of such …
Data-driven approximations of dynamical systems operators for control
Abstract The Koopman and Perron Frobenius transport operators are fundamentally
changing how we approach dynamical systems, providing linear representations for even …
changing how we approach dynamical systems, providing linear representations for even …
Feedback stabilization using Koopman operator
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 …
controllers for nonlinear control systems using the Koopman operator framework. The …
[HTML][HTML] Data-driven transient stability analysis using the Koopman operator
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 …
eigenfunction of the Koopman operator. We show that the Koopman eigenfunction with unit …
Data-driven optimal control via linear transfer operators: A convex approach
This paper is concerned with the data-driven optimal control of nonlinear systems. We
present a convex formulation of the optimal control problem with a discounted cost function …
present a convex formulation of the optimal control problem with a discounted cost function …