Results 81 to 90 of about 179,380 (196)

Dictionary learning in Extended Dynamic Mode Decomposition using a reservoir computer [PDF]

, 2019
We aim at improving extended dynamic mode decomposition that allows to linearize nonlinear systems.Indeed, the EDMD algorithm provides a finite-dimensional representation of the Koopman operator.Finally, the reservoir computer is trained to produce an efficient ...
Gulina, Marvyn, Mauroy, Alexandre
openaire   +1 more source

Application of noise-filtering techniques to data-driven analysis of electric power systems based on higher-order dynamic mode decomposition

International Journal of Electrical Power & Energy Systems
A transition to renewable energy is increasing the long-distance export of power, with reduced spinning inertia and small stability margins. In this work, we apply higher-order variants of a data-driven technique, the dynamic mode decomposition (DMD ...
C.N.S. Jones, S.V. Utyuzhnikov
doaj   +1 more source

Orthogonal polynomial approximation and Extended Dynamic Mode Decomposition in chaos

, 2023
Caroline L. Wormell
openalex   +2 more sources

K-SMPC: Koopman Operator-Based Stochastic Model Predictive Control for Enhanced Lateral Control of Autonomous Vehicles

IEEE Access
This paper proposes Koopman operator-based Stochastic Model Predictive Control (K-SMPC) for enhanced lateral control of autonomous vehicles. The Koopman operator is a linear map representing the nonlinear dynamics in an infinite-dimensional space.
Jin Sung Kim, Ying Shuai Quan, Chung Choo Chung, Woo Young Choi   +3 more
doaj   +1 more source

Consistent Dynamic Mode Decomposition

, 2019
We propose a new method for computing Dynamic Mode Decomposition (DMD) evolution matrices, which we use to analyze dynamical systems. Unlike the majority of existing methods, our approach is based on a variational formulation consisting of data alignment
Azencot, Omri, Bertozzi, Andrea, Yin, Wotao   +2 more
core  

Asymptotically stable data-driven koopman operator approximation with inputs using total extended DMD

Machine Learning: Science and Technology
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.
Louis Lortie, James Richard Forbes
doaj   +1 more source

Short-Term Voltage Stability Prediction for Power Systems Based on a Dominant Koopman Operator-Enhanced MLE

IEEE Access
Short-term voltage stability (STVS) prediction is a critical technology for modern power systems with high penetration of renewable energy resources. To address the limitations of the traditional maximum Lyapunov exponent (MLE) in handling short-time ...
Han Gao, Deyou Yang, Yanling Lv, Lixin Wang   +3 more
doaj   +1 more source

Extreme Short-Term Prediction of Unmanned Surface Vessel Nonlinear Motion Under Waves

Journal of Marine Science and Engineering
Under complex hydrodynamic conditions, Unmanned Surface Vessel (USV) exhibits non-stationary and nonlinear dynamic behaviors. Extreme short-term prediction of such nonlinear motion is therefore critical for ensuring navigational safety.
Yiwen Wang, Jian Li, Shan Wang, Hantao Zhang, Long Yang, Weiguo Wu   +5 more
doaj   +1 more source

On analytical construction of observable functions in extended dynamic mode decomposition for nonlinear estimation and prediction [PDF]

, 2021
Marcos Netto, Yoshihiko Susuki, Venkat Krishnan, Yingchen Zhang   +3 more
openalex   +1 more source

Low-rank Approximation of Linear Maps

, 2018
This work provides closed-form solutions and minimal achievable errors for a large class of low-rank approximation problems in Hilbert spaces. The proposed theorem generalizes to the case of linear bounded operators and p-th Schatten norms previous ...
Heas, Patrick, Herzet, Cedric
core