This paper introduces the Koopman Control Family (KCF), a mathematical framework for modeling general discrete-time nonlinear control systems with the aim of providing a solid theoretical foundation for the use of Koopman-based methods in systems with inputs. We demonstrate that the concept of KCF can completely capture the behavior of nonlinear control systems on a (potentially infinite-dimensional) function space. By employing a generalized notion of subspace invariance under the KCF, we establish a universal form for finite-dimensional models, which encompasses the commonly used linear, bilinear, and linear switched models as specific instances. In cases where the subspace is not invariant under the KCF, we propose a method for approxima...
Koopman analysis provides a general framework from which to analyze a nonlinear dynamical system in ...
We propose a novel framework for learning linear time-invariant (LTI) models for a class of continuo...
Dynamical systems representing vehicle flight are inherently nonlinear. Currently there are no gener...
This paper introduces the Koopman Control Family (KCF), a mathematical framework for modeling genera...
<div><p>In this work, we explore finite-dimensional linear representations of nonlinear dynamical sy...
System representations inspired by the infinite-dimensional Koopman operator (generator) are increas...
Recent theoretical developments in dynamical systems and machine learning have allowed researchers t...
A learning method is proposed for Koopman operator-based models with the goal of improving closed-lo...
The Koopman framework proposes a linear representation of finite-dimensional nonlinear systems throu...
We present a novel data-driven approach for learning linear representations of a class of stable non...
Ranging from natural phenomena such as biological and chemical systems to artificial technologies su...
We consider the problem of synthesis of safe controllers for nonlinear systems with unknown dynamics...
Within this work, we investigate how data-driven numerical approximation methods of the Koopman oper...
The Koopman operator provides a linear perspective on non-linear dynamics by focusing on the evoluti...
This dissertation studies the data-driven modeling and control problem of nonlinear systems by explo...
Koopman analysis provides a general framework from which to analyze a nonlinear dynamical system in ...
We propose a novel framework for learning linear time-invariant (LTI) models for a class of continuo...
Dynamical systems representing vehicle flight are inherently nonlinear. Currently there are no gener...
This paper introduces the Koopman Control Family (KCF), a mathematical framework for modeling genera...
<div><p>In this work, we explore finite-dimensional linear representations of nonlinear dynamical sy...
System representations inspired by the infinite-dimensional Koopman operator (generator) are increas...
Recent theoretical developments in dynamical systems and machine learning have allowed researchers t...
A learning method is proposed for Koopman operator-based models with the goal of improving closed-lo...
The Koopman framework proposes a linear representation of finite-dimensional nonlinear systems throu...
We present a novel data-driven approach for learning linear representations of a class of stable non...
Ranging from natural phenomena such as biological and chemical systems to artificial technologies su...
We consider the problem of synthesis of safe controllers for nonlinear systems with unknown dynamics...
Within this work, we investigate how data-driven numerical approximation methods of the Koopman oper...
The Koopman operator provides a linear perspective on non-linear dynamics by focusing on the evoluti...
This dissertation studies the data-driven modeling and control problem of nonlinear systems by explo...
Koopman analysis provides a general framework from which to analyze a nonlinear dynamical system in ...
We propose a novel framework for learning linear time-invariant (LTI) models for a class of continuo...
Dynamical systems representing vehicle flight are inherently nonlinear. Currently there are no gener...