Data-driven prediction in dynamical systems: recent developments

A Ghadami, BI Epureanu - Philosophical Transactions of …, 2022‏ - royalsocietypublishing.org
In recent years, we have witnessed a significant shift toward ever-more complex and ever-
larger-scale systems in the majority of the grand societal challenges tackled in applied …

Koopman operator dynamical models: Learning, analysis and control

P Bevanda, S Sosnowski, S Hirche - Annual Reviews in Control, 2021‏ - Elsevier
The Koopman operator allows for handling nonlinear systems through a globally linear
representation. In general, the operator is infinite-dimensional–necessitating finite …

The multiverse of dynamic mode decomposition algorithms

MJ Colbrook - arxiv preprint arxiv:2312.00137, 2023‏ - arxiv.org
Dynamic Mode Decomposition (DMD) is a popular data-driven analysis technique used to
decompose complex, nonlinear systems into a set of modes, revealing underlying patterns …

Multiplicative dynamic mode decomposition

N Boullé, MJ Colbrook - arxiv preprint arxiv:2405.05334, 2024‏ - arxiv.org
Koopman operators are infinite-dimensional operators that linearize nonlinear dynamical
systems, facilitating the study of their spectral properties and enabling the prediction of the …

Data-driven approximations of dynamical systems operators for control

E Kaiser, JN Kutz, SL Brunton - The Koopman operator in systems and …, 2020‏ - Springer
Abstract The Koopman and Perron Frobenius transport operators are fundamentally
changing how we approach dynamical systems, providing linear representations for even …

Feedback stabilization using Koopman operator

B Huang, X Ma, U Vaidya - 2018 IEEE Conference on Decision …, 2018‏ - ieeexplore.ieee.org
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 …

The future of control of process systems

P Daoutidis, L Megan, W Tang - Computers & Chemical Engineering, 2023‏ - Elsevier
This paper provides a perspective on the major challenges and directions in academic
process control research over the next 5–10 years, and its industrial implementation. Large …

A convex approach to data-driven optimal control via Perron–Frobenius and Koopman operators

B Huang, U Vaidya - IEEE Transactions on Automatic Control, 2022‏ - ieeexplore.ieee.org
This article is about the data-driven computation of optimal control for a class of control affine
deterministic nonlinear systems. We assume that the control dynamical system model is not …

On robust computation of koopman operator and prediction in random dynamical systems

S Sinha, B Huang, U Vaidya - Journal of Nonlinear Science, 2020‏ - Springer
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 …

Data-driven nonlinear stabilization using koopman operator

B Huang, X Ma, U Vaidya - The Koopman Operator in Systems and …, 2020‏ - Springer
We propose the application of Koopman operator theory for the design of stabilizing
feedback controller for a nonlinear control system. The proposed approach is data-driven …