Results 81 to 90 of about 212,072 (202)

Data-Driven Battery Modeling: Utilizing Dictionary Learning Extended Dynamic Mode Decomposition with Control

Lama S. Alshammari, Mohamed Badr, Otavio Bertozzi, Muhammad Zeeshan, Azza A. Faiad, Murali Sankar Venkatraman, Nuria Calvet, Shehab Ahmed   +7 more
openalex   +2 more sources

Meta-models of repeated dissipative joints for damping design phase [PDF]

, 2014
Developing tools to predict dissipation in mechanical assemblies starting from the design process is a subject of increasing interest. Design phases imply numerous computations resulting from the use of families of models with varying properties ...
BALMES, Etienne, HAMMAMI, Chaima
core   +3 more sources

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

Dynamic mode decomposition with control [PDF]

, 2014
We develop a new method which extends Dynamic Mode Decomposition (DMD) to incorporate the effect of control to extract low-order models from high-dimensional, complex systems.
Brunton, Steven L., Kutz, J. Nathan, Proctor, Joshua L.   +2 more
core  

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

Koopman Operator Theory for Infinite-Dimensional Systems: Extended Dynamic Mode Decomposition and Identification of Nonlinear PDEs [PDF]

, 2021
Alexandre Mauroy
openalex  

Extended Dynamic Mode Decomposition with Learned Koopman Eigenfunctions\n for Prediction and Control [PDF]

, 2019
Carl Folkestad, D. Pastor, Igor Mezić, Ryan Mohr, Maria Fonoberova, Joel W. Burdick   +5 more
openalex   +1 more source