Results 101 to 110 of about 1,745 (187)

Online Estimation of the Koopman Operator Using Fourier Features

, 2023
Transfer operators offer linear representations and global, physically meaningful features of nonlinear dynamical systems. Discovering transfer operators, such as the Koopman operator, require careful crafted dictionaries of observables, acting on states
Hsieh, M. Ani, Salam, Tahiya, Li, Alice Kate   +2 more
core  

Data-Driven Identification of Gas Turbine Engine Dynamics via Koopman Operator Genetic Algorithm

IEEE Access
Gas turbine engines (GTEs) are highly nonlinear control-nonaffine systems. Deriving their physics-based models can be challenging, particularly when some critical parameters can be difficult to measure or determine otherwise.
David Grasev
doaj   +1 more source

Using Signatures and Koopman Operator to Learn Nonlinear Dynamics

International audienceWe propose a novel framework for predicting the evolution of dynamical systems by learning the Koopman operator in the space of linear functionals on the Signature transform of trajectory data.
Chrétien, Stéphane, Patracone, Jordan, Gao, Ben, Alata, Olivier   +3 more
core   +3 more sources

Koopman Operator Theory and The Applied Perspective of Modern Data-Driven Systems

, 2022
Recent theoretical developments in dynamical systems and machine learning have allowed researchers to re-evaluate how dynamical systems are modeled and controlled.
Krolicki, Alex
core  

A deep Koopman operator‐based modelling approach for long‐term prediction of dynamics with pixel‐level measurements

CAAI Transactions on Intelligence Technology
Although previous studies have made some clear leap in learning latent dynamics from high‐dimensional representations, the performances in terms of accuracy and inference time of long‐term model prediction still need to be improved. In this study, a deep
Yongqian Xiao, Zixin Tang, Xin Xu, Xinglong Zhang, Yifei Shi   +4 more
doaj   +1 more source

Optimal Control of Entity-Based Systems via Koopman Representations With Product Density Observables

IEEE Open Journal of Control Systems
The Koopman operator, which describes a dynamical system via a linear representation that can be approximately learned from data, allows application of linear control techniques to nonlinear systems.
Madeline Blischke, Joao P. Hespanha
doaj   +1 more source

Koopman Operator Based Modeling and Control of Quadrotors

This book showcases a collection of papers that present cutting-edge studies, methods, experiments, and applications in various interdisciplinary fields. These fields encompass optimal control, guidance, navigation, game theory, stability, nonlinear dynamics, robotics, sensor fusion, machine learning, and autonomy. The chapters reveal novel studies and
Simone Martini, Alessandro Rizzo, Margareta Stefanovic, Patrizia Livreri, Matthew J. Rutherford, Kimon P. Valavanis   +5 more
openaire   +2 more sources

Heterogeneous Mixtures of Dictionary Functions to Approximate Subspace Invariance in Koopman Operators: Why Deep Koopman Operators Work

Journal of Nonlinear Science
Abstract Koopman operators model nonlinear dynamics as a linear dynamic system acting on a nonlinear function as the state. This nonstandard state is often called a Koopman observable and is usually approximated numerically by a superposition of functions drawn from a dictionary. In a widely used algorithm, extended dynamic mode decomposition
Charles A. Johnson, Shara Balakrishnan, Enoch Yeung   +2 more
openaire   +2 more sources

Koopman Spectral Linearization vs. Carleman Linearization: A Computational Comparison Study

Mathematics
Nonlinearity presents a significant challenge in developing quantum algorithms involving differential equations, prompting the exploration of various linearization techniques, including the well-known Carleman Linearization.
Dongwei Shi, Xiu Yang
doaj   +1 more source

Koopman fault‐tolerant model predictive control

IET Control Theory & Applications
This paper introduces a novel data‐driven approach to develop a fault‐tolerant model predictive controller (MPC) for non‐linear systems. By adopting a Koopman operator‐theoretic perspective, the proposed method leverages historical data from the system ...
Mohammadhosein Bakhtiaridoust, Meysam Yadegar, Fatemeh Jahangiri   +2 more
doaj   +1 more source