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The field of dynamical systems is being transformed by the mathematical tools and algorithms emerging from modern computing and data science. First-principles derivations and asymptotic reductions are giving way to data-driven approaches…

Dynamical Systems · Mathematics 2021-11-02 Steven L. Brunton , Marko Budišić , Eurika Kaiser , J. Nathan Kutz

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 Koopman operator approach provides a linear representation for a…

Optimization and Control · Mathematics 2018-10-02 Bowen Huang , Xu Ma , Umesh Vaidya

This paper provides sufficient conditions for global asymptotic stability and global exponential stability, which can be applied to nonlinear, large-scale, uncertain discrete-time systems. The conditions are derived by means of vector…

Optimization and Control · Mathematics 2014-03-25 Iasson Karafyllis , Markos Papageorgiou

We present a novel data-driven approach for learning linear representations of a class of stable nonlinear systems using Koopman eigenfunctions. By learning the conjugacy map between a nonlinear system and its Jacobian linearization through…

Machine Learning · Computer Science 2022-05-31 Petar Bevanda , Johannes Kirmayr , Stefan Sosnowski , Sandra Hirche

This paper considers the problem of robust stability for a class of uncertain quantum systems subject to unknown perturbations in the system coupling operator. A general stability result is given for a class of perturbations to the system…

Quantum Physics · Physics 2012-08-31 Ian R. Petersen , Valery Ugrinovskii , Matthew R. James

Gas turbine engines are complex and highly nonlinear dynamical systems. Deriving their physics-based models can be challenging because it requires performance characteristics that are not always available, often leading to many simplifying…

Machine Learning · Computer Science 2026-02-11 David Grasev

This paper proposes a mode-in-state contribution factor for a class of nonlinear dynamical systems by utilizing spectral properties of the Koopman operator and sensitivity analysis. Using eigenfunctions of the Koopman operator for a target…

Systems and Control · Electrical Eng. & Systems 2022-05-24 Kenji Takamichi , Yoshihiko Susuki , Marcos Netto , Atsushi Ishigame

The Koopman operator framework can be used to identify a data-driven model of a nonlinear system. Unfortunately, when the data is corrupted by noise, the identified model can be biased. Additionally, depending on the choice of lifting…

Systems and Control · Electrical Eng. & Systems 2024-09-02 Louis Lortie , James Richard Forbes

In recent years data-driven analysis of dynamical systems has attracted a lot of attention and transfer operator techniques, namely, Perron-Frobenius and Koopman operators are being used almost ubiquitously. Since data is always obtained in…

Systems and Control · Electrical Eng. & Systems 2022-03-29 Subhrajit Sinha , Sai Pushpak Nandanoori , Jan Drgona , Draguna Vrabie

We solve the problem of output feedback stabilization of a class of nonlinear systems, which may have unstable zero dynamics. We allow for any globally stabilizing full state feedback control scheme to be used as long as it satisfies a…

Systems and Control · Computer Science 2016-07-26 Almuatazbellah M. Boker , Hassan K. Khalil

The generalization of the Koopman operator to systems with control input and the derivation of a nonlinear fundamental lemma are two open problems that play a key role in the development of data-driven control methods for nonlinear systems.…

Optimization and Control · Mathematics 2026-03-25 Mircea Lazar

The aim of this paper is to establish the $H^1$ global well-posedness for Kirchhoff systems. The new approach to the construction of solutions is based on the asymptotic integrations for strictly hyperbolic systems with time-dependent…

Analysis of PDEs · Mathematics 2014-01-14 Tokio Matsuyama , Michael Ruzhansky

The Koopman operator is a linear but infinite dimensional operator that governs the evolution of scalar observables defined on the state space of an autonomous dynamical system, and is a powerful tool for the analysis and decomposition of…

Dynamical Systems · Mathematics 2015-07-28 Matthew O. Williams , Ioannis G. Kevrekidis , Clarence W. Rowley

In this report we deal with the problem of global output feedback stabilization of a class of $n$-dimensional nonlinear positive systems possessing a one-dimensional unknown, though measured, part. We first propose our main result, an…

Optimization and Control · Mathematics 2016-08-16 Jean-Luc Gouzé , Olivier Bernard , Ludovic Mailleret

This paper describes the optimal selection of a control policy to program the steady state of controlled nonlinear systems with hyperbolic fixed points. This work is motivated by the field of synthetic biology, in which saddle points are…

Dynamical Systems · Mathematics 2020-06-11 Aqib Hasnain , Nibodh Boddupalli , Shara Balakrishnan , Enoch Yeung

The cosmological dynamics are rigorously investigated through the systematic application of autonomous system analysis to the gravitational field equations in non-metricity gravity. The systematic procedure to analyze the late-time cosmic…

General Relativity and Quantum Cosmology · Physics 2025-03-13 Pooja Vishwakarma , Parth Shah , Kazuharu Bamba

Koopman operator describes evolution of observables in the phase space, which could be used to extract characteristic dynamical features of a nonlinear system. Here, we show that it is possible to carry out interesting symbolic partitions…

Chaotic Dynamics · Physics 2020-07-23 Cong Zhang , Yueheng Lan

A Koopman decomposition of a complex system leads to a representation in which nonlinear dynamics appear to be linear. The existence of a linear framework with which to analyse nonlinear dynamical systems brings new strategies for…

Fluid Dynamics · Physics 2019-03-12 Jeremy Parker , Jacob Page

This paper introduces a framework for solving time-autonomous nonlinear infinite horizon optimal control problems, under the assumption that all minimizers satisfy Pontryagin's necessary optimality conditions. In detail, we use methods from…

Optimization and Control · Mathematics 2020-03-04 Mario E. Villanueva , Colin Jones , Boris Houska

Recently, Koopman operator theory has become a powerful tool for developing linear representations of non-linear dynamical systems. However, existing data-driven applications of Koopman operator theory, including both traditional and deep…

Machine Learning · Computer Science 2023-05-17 King Fai Yeh , Paris Flood , William Redman , Pietro Liò
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